X-Git-Url: https://pintos-os.org/cgi-bin/gitweb.cgi?a=blobdiff_plain;f=src%2Flanguage%2Fstats%2Foneway.c;h=6ad71f14c829fc75a91b63e89854f18d9fc3b179;hb=f4491cda2715c59495d963d0a3d8ae4518c1c13d;hp=f390a3c8aa5a3a420bb9c0cf0c207013f70f6e12;hpb=44a9abb173e2b0f33b011a853ae1603fda0ce29b;p=pspp diff --git a/src/language/stats/oneway.c b/src/language/stats/oneway.c index f390a3c8aa..6ad71f14c8 100644 --- a/src/language/stats/oneway.c +++ b/src/language/stats/oneway.c @@ -1,5 +1,6 @@ /* PSPP - a program for statistical analysis. - Copyright (C) 1997-9, 2000, 2007, 2009, 2010 Free Software Foundation, Inc. + Copyright (C) 1997-9, 2000, 2007, 2009, 2010, 2011, 2012, 2013, 2014, + 2020 Free Software Foundation, Inc. This program is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by @@ -16,44 +17,68 @@ #include -#include -#include -#include -#include -#include -#include - - -#include -#include -#include -#include +#include +#include #include -#include +#include -#include +#include "data/case.h" +#include "data/casegrouper.h" +#include "data/casereader.h" +#include "data/dataset.h" +#include "data/dictionary.h" +#include "data/format.h" +#include "data/value.h" +#include "language/command.h" +#include "language/dictionary/split-file.h" +#include "language/lexer/lexer.h" +#include "language/lexer/value-parser.h" +#include "language/lexer/variable-parser.h" +#include "libpspp/ll.h" +#include "libpspp/message.h" +#include "libpspp/misc.h" +#include "libpspp/taint.h" +#include "linreg/sweep.h" +#include "tukey/tukey.h" +#include "math/categoricals.h" +#include "math/interaction.h" +#include "math/covariance.h" +#include "math/levene.h" +#include "math/moments.h" +#include "output/pivot-table.h" -#include -#include -#include -#include +#include "gettext.h" +#define _(msgid) gettext (msgid) +#define N_(msgid) msgid +/* Workspace variable for each dependent variable */ +struct per_var_ws +{ + struct interaction *iact; + struct categoricals *cat; + struct covariance *cov; + struct levene *nl; -#include -#include -#include + double n; -#include + double sst; + double sse; + double ssa; -#include -#include -#include + int n_groups; -#include + double mse; +}; -#include "gettext.h" -#define _(msgid) gettext (msgid) +/* Per category data */ +struct descriptive_data +{ + const struct variable *var; + struct moments1 *mom; + double minimum; + double maximum; +}; enum missing_type { @@ -69,17 +94,37 @@ enum statistics struct coeff_node { - struct ll ll; - double coeff; + struct ll ll; + double coeff; }; struct contrasts_node { - struct ll ll; + struct ll ll; struct ll_list coefficient_list; +}; + + +struct oneway_spec; + +typedef double df_func (const struct per_var_ws *pvw, const struct moments1 *mom_i, const struct moments1 *mom_j); +typedef double ts_func (int k, const struct moments1 *mom_i, const struct moments1 *mom_j, double std_err); +typedef double p1tail_func (double ts, double df1, double df2); + +typedef double pinv_func (double std_err, double alpha, double df, int k, const struct moments1 *mom_i, const struct moments1 *mom_j); + + +struct posthoc +{ + const char *syntax; + const char *label; + + df_func *dff; + ts_func *tsf; + p1tail_func *p1f; - bool bad_count; /* True if the number of coefficients does not equal the number of groups */ + pinv_func *pinv; }; struct oneway_spec @@ -99,34 +144,229 @@ struct oneway_spec /* The weight variable */ const struct variable *wv; + const struct fmt_spec *wfmt; + /* The confidence level for multiple comparisons */ + double alpha; + + int *posthoc; + int n_posthoc; }; -/* Per category data */ -struct descriptive_data +static double +df_common (const struct per_var_ws *pvw, const struct moments1 *mom_i UNUSED, const struct moments1 *mom_j UNUSED) { - const struct variable *var; - struct moments1 *mom; + return pvw->n - pvw->n_groups; +} - double minimum; - double maximum; -}; +static double +df_individual (const struct per_var_ws *pvw UNUSED, const struct moments1 *mom_i, const struct moments1 *mom_j) +{ + double n_i, var_i; + double n_j, var_j; + double nom,denom; -/* Workspace variable for each dependent variable */ -struct per_var_ws + moments1_calculate (mom_i, &n_i, NULL, &var_i, 0, 0); + moments1_calculate (mom_j, &n_j, NULL, &var_j, 0, 0); + + if (n_i <= 1.0 || n_j <= 1.0) + return SYSMIS; + + nom = pow2 (var_i/n_i + var_j/n_j); + denom = pow2 (var_i/n_i) / (n_i - 1) + pow2 (var_j/n_j) / (n_j - 1); + + return nom / denom; +} + +static double lsd_pinv (double std_err, double alpha, double df, int k UNUSED, const struct moments1 *mom_i UNUSED, const struct moments1 *mom_j UNUSED) { - struct categoricals *cat; - struct covariance *cov; + return std_err * gsl_cdf_tdist_Pinv (1.0 - alpha / 2.0, df); +} - double sst; - double sse; - double ssa; +static double bonferroni_pinv (double std_err, double alpha, double df, int k, const struct moments1 *mom_i UNUSED, const struct moments1 *mom_j UNUSED) +{ + const int m = k * (k - 1) / 2; + return std_err * gsl_cdf_tdist_Pinv (1.0 - alpha / (2.0 * m), df); +} - int n_groups; +static double sidak_pinv (double std_err, double alpha, double df, int k, const struct moments1 *mom_i UNUSED, const struct moments1 *mom_j UNUSED) +{ + const double m = k * (k - 1) / 2; + double lp = 1.0 - exp (log (1.0 - alpha) / m) ; + return std_err * gsl_cdf_tdist_Pinv (1.0 - lp / 2.0, df); +} + +static double tukey_pinv (double std_err, double alpha, double df, int k, const struct moments1 *mom_i UNUSED, const struct moments1 *mom_j UNUSED) +{ + if (k < 2 || df < 2) + return SYSMIS; + + return std_err / sqrt (2.0) * qtukey (1 - alpha, 1.0, k, df, 1, 0); +} + +static double scheffe_pinv (double std_err, double alpha, double df, int k, const struct moments1 *mom_i UNUSED, const struct moments1 *mom_j UNUSED) +{ + double x = (k - 1) * gsl_cdf_fdist_Pinv (1.0 - alpha, k - 1, df); + return std_err * sqrt (x); +} + +static double gh_pinv (double std_err UNUSED, double alpha, double df, int k, const struct moments1 *mom_i, const struct moments1 *mom_j) +{ + double n_i, mean_i, var_i; + double n_j, mean_j, var_j; + double m; + + moments1_calculate (mom_i, &n_i, &mean_i, &var_i, 0, 0); + moments1_calculate (mom_j, &n_j, &mean_j, &var_j, 0, 0); + + m = sqrt ((var_i/n_i + var_j/n_j) / 2.0); + + if (k < 2 || df < 2) + return SYSMIS; + + return m * qtukey (1 - alpha, 1.0, k, df, 1, 0); +} + + +static double +multiple_comparison_sig (double std_err, + const struct per_var_ws *pvw, + const struct descriptive_data *dd_i, const struct descriptive_data *dd_j, + const struct posthoc *ph) +{ + int k = pvw->n_groups; + double df = ph->dff (pvw, dd_i->mom, dd_j->mom); + double ts = ph->tsf (k, dd_i->mom, dd_j->mom, std_err); + if (df == SYSMIS) + return SYSMIS; + return ph->p1f (ts, k - 1, df); +} + +static double +mc_half_range (const struct oneway_spec *cmd, const struct per_var_ws *pvw, double std_err, const struct descriptive_data *dd_i, const struct descriptive_data *dd_j, const struct posthoc *ph) +{ + int k = pvw->n_groups; + double df = ph->dff (pvw, dd_i->mom, dd_j->mom); + if (df == SYSMIS) + return SYSMIS; + + return ph->pinv (std_err, cmd->alpha, df, k, dd_i->mom, dd_j->mom); +} + +static double tukey_1tailsig (double ts, double df1, double df2) +{ + double twotailedsig; + + if (df2 < 2 || df1 < 1) + return SYSMIS; + + twotailedsig = 1.0 - ptukey (ts, 1.0, df1 + 1, df2, 1, 0); + + return twotailedsig / 2.0; +} + +static double lsd_1tailsig (double ts, double df1 UNUSED, double df2) +{ + return ts < 0 ? gsl_cdf_tdist_P (ts, df2) : gsl_cdf_tdist_Q (ts, df2); +} + +static double sidak_1tailsig (double ts, double df1, double df2) +{ + double ex = (df1 + 1.0) * df1 / 2.0; + double lsd_sig = 2 * lsd_1tailsig (ts, df1, df2); + + return 0.5 * (1.0 - pow (1.0 - lsd_sig, ex)); +} + +static double bonferroni_1tailsig (double ts, double df1, double df2) +{ + const int m = (df1 + 1) * df1 / 2; + + double p = ts < 0 ? gsl_cdf_tdist_P (ts, df2) : gsl_cdf_tdist_Q (ts, df2); + p *= m; + + return p > 0.5 ? 0.5 : p; +} + +static double scheffe_1tailsig (double ts, double df1, double df2) +{ + return 0.5 * gsl_cdf_fdist_Q (ts, df1, df2); +} + + +static double tukey_test_stat (int k UNUSED, const struct moments1 *mom_i, const struct moments1 *mom_j, double std_err) +{ + double ts; + double n_i, mean_i, var_i; + double n_j, mean_j, var_j; + + moments1_calculate (mom_i, &n_i, &mean_i, &var_i, 0, 0); + moments1_calculate (mom_j, &n_j, &mean_j, &var_j, 0, 0); + + ts = (mean_i - mean_j) / std_err; + ts = fabs (ts) * sqrt (2.0); + + return ts; +} + +static double lsd_test_stat (int k UNUSED, const struct moments1 *mom_i, const struct moments1 *mom_j, double std_err) +{ + double n_i, mean_i, var_i; + double n_j, mean_j, var_j; + + moments1_calculate (mom_i, &n_i, &mean_i, &var_i, 0, 0); + moments1_calculate (mom_j, &n_j, &mean_j, &var_j, 0, 0); + + return (mean_i - mean_j) / std_err; +} + +static double scheffe_test_stat (int k, const struct moments1 *mom_i, const struct moments1 *mom_j, double std_err) +{ + double t; + double n_i, mean_i, var_i; + double n_j, mean_j, var_j; + + moments1_calculate (mom_i, &n_i, &mean_i, &var_i, 0, 0); + moments1_calculate (mom_j, &n_j, &mean_j, &var_j, 0, 0); + + t = (mean_i - mean_j) / std_err; + t = pow2 (t); + t /= k - 1; + + return t; +} + +static double gh_test_stat (int k UNUSED, const struct moments1 *mom_i, const struct moments1 *mom_j, double std_err UNUSED) +{ + double ts; + double thing; + double n_i, mean_i, var_i; + double n_j, mean_j, var_j; + + moments1_calculate (mom_i, &n_i, &mean_i, &var_i, 0, 0); + moments1_calculate (mom_j, &n_j, &mean_j, &var_j, 0, 0); + + thing = var_i / n_i + var_j / n_j; + thing /= 2.0; + thing = sqrt (thing); + + ts = (mean_i - mean_j) / thing; + + return fabs (ts); +} + + + +static const struct posthoc ph_tests [] = + { + { "LSD", N_("LSD"), df_common, lsd_test_stat, lsd_1tailsig, lsd_pinv}, + { "TUKEY", N_("Tukey HSD"), df_common, tukey_test_stat, tukey_1tailsig, tukey_pinv}, + { "BONFERRONI", N_("Bonferroni"), df_common, lsd_test_stat, bonferroni_1tailsig, bonferroni_pinv}, + { "SCHEFFE", N_("Scheffé"), df_common, scheffe_test_stat, scheffe_1tailsig, scheffe_pinv}, + { "GH", N_("Games-Howell"), df_individual, gh_test_stat, tukey_1tailsig, gh_pinv}, + { "SIDAK", N_("Šidák"), df_common, lsd_test_stat, sidak_1tailsig, sidak_pinv} + }; - double mse; - double levene_w; -}; struct oneway_workspace { @@ -148,10 +388,41 @@ static void show_homogeneity (const struct oneway_spec *, const struct oneway_wo static void output_oneway (const struct oneway_spec *, struct oneway_workspace *ws); static void run_oneway (const struct oneway_spec *cmd, struct casereader *input, const struct dataset *ds); + +static void +destroy_coeff_list (struct contrasts_node *coeff_list) +{ + struct coeff_node *cn = NULL; + struct coeff_node *cnx = NULL; + struct ll_list *cl = &coeff_list->coefficient_list; + + ll_for_each_safe (cn, cnx, struct coeff_node, ll, cl) + { + free (cn); + } + + free (coeff_list); +} + +static void +oneway_cleanup (struct oneway_spec *cmd) +{ + struct contrasts_node *coeff_list = NULL; + struct contrasts_node *coeff_next = NULL; + ll_for_each_safe (coeff_list, coeff_next, struct contrasts_node, ll, &cmd->contrast_list) + { + destroy_coeff_list (coeff_list); + } + + free (cmd->posthoc); +} + + + int cmd_oneway (struct lexer *lexer, struct dataset *ds) { - const struct dictionary *dict = dataset_dict (ds); + const struct dictionary *dict = dataset_dict (ds); struct oneway_spec oneway ; oneway.n_vars = 0; oneway.vars = NULL; @@ -160,11 +431,15 @@ cmd_oneway (struct lexer *lexer, struct dataset *ds) oneway.missing_type = MISS_ANALYSIS; oneway.exclude = MV_ANY; oneway.wv = dict_get_weight (dict); + oneway.wfmt = dict_get_weight_format (dict); + oneway.alpha = 0.05; + oneway.posthoc = NULL; + oneway.n_posthoc = 0; ll_init (&oneway.contrast_list); - - if ( lex_match (lexer, T_SLASH)) + + if (lex_match (lexer, T_SLASH)) { if (!lex_force_match_id (lexer, "VARIABLES")) { @@ -178,9 +453,12 @@ cmd_oneway (struct lexer *lexer, struct dataset *ds) PV_NO_DUPLICATE | PV_NUMERIC)) goto error; - lex_force_match (lexer, T_BY); + if (!lex_force_match (lexer, T_BY)) + goto error; oneway.indep_var = parse_variable_const (lexer, dict); + if (oneway.indep_var == NULL) + goto error; while (lex_token (lexer) != T_ENDCMD) { @@ -206,9 +484,49 @@ cmd_oneway (struct lexer *lexer, struct dataset *ds) } } } + else if (lex_match_id (lexer, "POSTHOC")) + { + lex_match (lexer, T_EQUALS); + while (lex_token (lexer) != T_ENDCMD && lex_token (lexer) != T_SLASH) + { + int p; + bool method = false; + for (p = 0 ; p < sizeof (ph_tests) / sizeof (struct posthoc); ++p) + { + if (lex_match_id (lexer, ph_tests[p].syntax)) + { + oneway.n_posthoc++; + oneway.posthoc = xrealloc (oneway.posthoc, sizeof (*oneway.posthoc) * oneway.n_posthoc); + oneway.posthoc[oneway.n_posthoc - 1] = p; + method = true; + break; + } + } + if (method == false) + { + if (lex_match_id (lexer, "ALPHA")) + { + if (!lex_force_match (lexer, T_LPAREN)) + goto error; + if (! lex_force_num (lexer)) + goto error; + oneway.alpha = lex_number (lexer); + lex_get (lexer); + if (!lex_force_match (lexer, T_RPAREN)) + goto error; + } + else + { + msg (SE, _("The post hoc analysis method %s is not supported."), lex_tokcstr (lexer)); + lex_error (lexer, NULL); + goto error; + } + } + } + } else if (lex_match_id (lexer, "CONTRAST")) { - struct contrasts_node *cl = xzalloc (sizeof *cl); + struct contrasts_node *cl = XZALLOC (struct contrasts_node); struct ll_list *coefficient_list = &cl->coefficient_list; lex_match (lexer, T_EQUALS); @@ -217,7 +535,7 @@ cmd_oneway (struct lexer *lexer, struct dataset *ds) while (lex_token (lexer) != T_ENDCMD && lex_token (lexer) != T_SLASH) { - if ( lex_is_number (lexer)) + if (lex_is_number (lexer)) { struct coeff_node *cc = xmalloc (sizeof *cc); cc->coeff = lex_number (lexer); @@ -227,11 +545,18 @@ cmd_oneway (struct lexer *lexer, struct dataset *ds) } else { + destroy_coeff_list (cl); lex_error (lexer, NULL); goto error; } } + if (ll_count (coefficient_list) <= 0) + { + destroy_coeff_list (cl); + goto error; + } + ll_push_tail (&oneway.contrast_list, &cl->ll); } else if (lex_match_id (lexer, "MISSING")) @@ -282,10 +607,12 @@ cmd_oneway (struct lexer *lexer, struct dataset *ds) ok = proc_commit (ds) && ok; } + oneway_cleanup (&oneway); free (oneway.vars); return CMD_SUCCESS; error: + oneway_cleanup (&oneway); free (oneway.vars); return CMD_FAILURE; } @@ -315,7 +642,7 @@ dd_destroy (struct descriptive_data *dd) } static void * -makeit (void *aux1, void *aux2 UNUSED) +makeit (const void *aux1, void *aux2 UNUSED) { const struct variable *var = aux1; @@ -324,28 +651,26 @@ makeit (void *aux1, void *aux2 UNUSED) return dd; } -static void -updateit (void *user_data, - enum mv_class exclude, - const struct variable *wv, - const struct variable *catvar UNUSED, - const struct ccase *c, - void *aux1, void *aux2) +static void +killit (const void *aux1 UNUSED, void *aux2 UNUSED, void *user_data) { struct descriptive_data *dd = user_data; - const struct variable *varp = aux1; + dd_destroy (dd); +} - const union value *valx = case_data (c, varp); - struct descriptive_data *dd_total = aux2; +static void +updateit (const void *aux1, void *aux2, void *user_data, + const struct ccase *c, double weight) +{ + struct descriptive_data *dd = user_data; - double weight; + const struct variable *varp = aux1; - if ( var_is_value_missing (varp, valx, exclude)) - return; + const union value *valx = case_data (c, varp); - weight = wv != NULL ? case_data (c, wv)->f : 1.0; + struct descriptive_data *dd_total = aux2; moments1_add (dd->mom, valx->f, weight); if (valx->f < dd->minimum) @@ -384,23 +709,35 @@ run_oneway (const struct oneway_spec *cmd, struct oneway_workspace ws; ws.actual_number_of_groups = 0; - ws.vws = xzalloc (cmd->n_vars * sizeof (*ws.vws)); - ws.dd_total = xmalloc (sizeof (struct descriptive_data) * cmd->n_vars); + ws.vws = xcalloc (cmd->n_vars, sizeof (*ws.vws)); + ws.dd_total = XCALLOC (cmd->n_vars, struct descriptive_data*); for (v = 0 ; v < cmd->n_vars; ++v) ws.dd_total[v] = dd_create (cmd->vars[v]); for (v = 0; v < cmd->n_vars; ++v) { - ws.vws[v].cat = categoricals_create (&cmd->indep_var, 1, cmd->wv, - cmd->exclude, makeit, updateit, - CONST_CAST (struct variable *, - cmd->vars[v]), - ws.dd_total[v]); + static const struct payload payload = + { + .create = makeit, + .update = updateit, + .calculate = NULL, + .destroy = killit + }; + + ws.vws[v].iact = interaction_create (cmd->indep_var); + ws.vws[v].cat = categoricals_create (&ws.vws[v].iact, 1, cmd->wv, + cmd->exclude); + + categoricals_set_payload (ws.vws[v].cat, &payload, + CONST_CAST (struct variable *, cmd->vars[v]), + ws.dd_total[v]); + ws.vws[v].cov = covariance_2pass_create (1, &cmd->vars[v], - ws.vws[v].cat, - cmd->wv, cmd->exclude); + ws.vws[v].cat, + cmd->wv, cmd->exclude, true); + ws.vws[v].nl = levene_create (var_get_width (cmd->indep_var), NULL); } c = casereader_peek (input, 0); @@ -421,20 +758,11 @@ run_oneway (const struct oneway_spec *cmd, cmd->exclude, NULL, NULL); input = casereader_create_filter_weight (input, dict, NULL, NULL); - - if (cmd->stats & STATS_HOMOGENEITY) - for (v = 0; v < cmd->n_vars; ++v) - { - struct per_var_ws *pvw = &ws.vws[v]; - - pvw->levene_w = levene (input, cmd->indep_var, cmd->vars[v], cmd->wv, cmd->exclude); - } - reader = casereader_clone (input); - for (; (c = casereader_read (reader)) != NULL; case_unref (c)) { int i; + double w = dict_get_case_weight (dict, c, NULL); for (i = 0; i < cmd->n_vars; ++i) { @@ -442,69 +770,113 @@ run_oneway (const struct oneway_spec *cmd, const struct variable *v = cmd->vars[i]; const union value *val = case_data (c, v); - if ( MISS_ANALYSIS == cmd->missing_type) + if (MISS_ANALYSIS == cmd->missing_type) { - if ( var_is_value_missing (v, val, cmd->exclude)) + if (var_is_value_missing (v, val) & cmd->exclude) continue; } covariance_accumulate_pass1 (pvw->cov, c); + levene_pass_one (pvw->nl, val->f, w, case_data (c, cmd->indep_var)); } } casereader_destroy (reader); + reader = casereader_clone (input); - for ( ; (c = casereader_read (reader) ); case_unref (c)) + for (; (c = casereader_read (reader)); case_unref (c)) { int i; + double w = dict_get_case_weight (dict, c, NULL); for (i = 0; i < cmd->n_vars; ++i) { struct per_var_ws *pvw = &ws.vws[i]; const struct variable *v = cmd->vars[i]; const union value *val = case_data (c, v); - if ( MISS_ANALYSIS == cmd->missing_type) + if (MISS_ANALYSIS == cmd->missing_type) { - if ( var_is_value_missing (v, val, cmd->exclude)) + if (var_is_value_missing (v, val) & cmd->exclude) continue; } covariance_accumulate_pass2 (pvw->cov, c); + levene_pass_two (pvw->nl, val->f, w, case_data (c, cmd->indep_var)); } } casereader_destroy (reader); + reader = casereader_clone (input); + for (; (c = casereader_read (reader)); case_unref (c)) + { + int i; + double w = dict_get_case_weight (dict, c, NULL); + + for (i = 0; i < cmd->n_vars; ++i) + { + struct per_var_ws *pvw = &ws.vws[i]; + const struct variable *v = cmd->vars[i]; + const union value *val = case_data (c, v); + + if (MISS_ANALYSIS == cmd->missing_type) + { + if (var_is_value_missing (v, val) & cmd->exclude) + continue; + } + + levene_pass_three (pvw->nl, val->f, w, case_data (c, cmd->indep_var)); + } + } + casereader_destroy (reader); + + for (v = 0; v < cmd->n_vars; ++v) { + const gsl_matrix *ucm; + gsl_matrix *cm; struct per_var_ws *pvw = &ws.vws[v]; - gsl_matrix *cm = covariance_calculate_unnormalized (pvw->cov); const struct categoricals *cats = covariance_get_categoricals (pvw->cov); + const bool ok = categoricals_sane (cats); - double n; - moments1_calculate (ws.dd_total[v]->mom, &n, NULL, NULL, NULL, NULL); + if (! ok) + { + msg (MW, + _("Dependent variable %s has no non-missing values. No analysis for this variable will be done."), + var_get_name (cmd->vars[v])); + continue; + } - pvw->sst = gsl_matrix_get (cm, 0, 0); + ucm = covariance_calculate_unnormalized (pvw->cov); - // gsl_matrix_fprintf (stdout, cm, "%g "); + cm = gsl_matrix_alloc (ucm->size1, ucm->size2); + gsl_matrix_memcpy (cm, ucm); + + moments1_calculate (ws.dd_total[v]->mom, &pvw->n, NULL, NULL, NULL, NULL); + + pvw->sst = gsl_matrix_get (cm, 0, 0); reg_sweep (cm, 0); pvw->sse = gsl_matrix_get (cm, 0, 0); + gsl_matrix_free (cm); pvw->ssa = pvw->sst - pvw->sse; - pvw->n_groups = categoricals_total (cats); + pvw->n_groups = categoricals_n_total (cats); - pvw->mse = (pvw->sst - pvw->ssa) / (n - pvw->n_groups); + pvw->mse = (pvw->sst - pvw->ssa) / (pvw->n - pvw->n_groups); } for (v = 0; v < cmd->n_vars; ++v) { - struct categoricals *cats = covariance_get_categoricals (ws.vws[v].cov); + const struct categoricals *cats = covariance_get_categoricals (ws.vws[v].cov); - categoricals_done (cats); - - if (categoricals_total (cats) > ws.actual_number_of_groups) - ws.actual_number_of_groups = categoricals_total (cats); + if (! categoricals_is_complete (cats)) + { + continue; + } + + if (categoricals_n_total (cats) > ws.actual_number_of_groups) + ws.actual_number_of_groups = categoricals_n_total (cats); } casereader_destroy (input); @@ -515,18 +887,22 @@ run_oneway (const struct oneway_spec *cmd, taint_destroy (taint); finish: + for (v = 0; v < cmd->n_vars; ++v) { covariance_destroy (ws.vws[v].cov); + levene_destroy (ws.vws[v].nl); dd_destroy (ws.dd_total[v]); + interaction_destroy (ws.vws[v].iact); } + free (ws.vws); free (ws.dd_total); - } static void show_contrast_coeffs (const struct oneway_spec *cmd, const struct oneway_workspace *ws); static void show_contrast_tests (const struct oneway_spec *cmd, const struct oneway_workspace *ws); +static void show_comparisons (const struct oneway_spec *cmd, const struct oneway_workspace *ws, int depvar); static void output_oneway (const struct oneway_spec *cmd, struct oneway_workspace *ws) @@ -535,7 +911,8 @@ output_oneway (const struct oneway_spec *cmd, struct oneway_workspace *ws) /* Check the sanity of the given contrast values */ struct contrasts_node *coeff_list = NULL; - ll_for_each (coeff_list, struct contrasts_node, ll, &cmd->contrast_list) + struct contrasts_node *coeff_next = NULL; + ll_for_each_safe (coeff_list, coeff_next, struct contrasts_node, ll, &cmd->contrast_list) { struct coeff_node *cn = NULL; double sum = 0; @@ -545,15 +922,18 @@ output_oneway (const struct oneway_spec *cmd, struct oneway_workspace *ws) if (ll_count (cl) != ws->actual_number_of_groups) { msg (SW, - _("Number of contrast coefficients must equal the number of groups")); - coeff_list->bad_count = true; + _("In contrast list %zu, the number of coefficients (%zu) does not equal the number of groups (%d). This contrast list will be ignored."), + i, ll_count (cl), ws->actual_number_of_groups); + + ll_remove (&coeff_list->ll); + destroy_coeff_list (coeff_list); continue; } ll_for_each (cn, struct coeff_node, ll, cl) sum += cn->coeff; - if ( sum != 0.0 ) + if (sum != 0.0) msg (SW, _("Coefficients for contrast %zu do not total zero"), i); } @@ -570,6 +950,18 @@ output_oneway (const struct oneway_spec *cmd, struct oneway_workspace *ws) show_contrast_coeffs (cmd, ws); show_contrast_tests (cmd, ws); } + + if (cmd->posthoc) + { + int v; + for (v = 0 ; v < cmd->n_vars; ++v) + { + const struct categoricals *cats = covariance_get_categoricals (ws->vws[v].cov); + + if (categoricals_is_complete (cats)) + show_comparisons (cmd, ws, v); + } + } } @@ -577,303 +969,220 @@ output_oneway (const struct oneway_spec *cmd, struct oneway_workspace *ws) static void show_anova_table (const struct oneway_spec *cmd, const struct oneway_workspace *ws) { - size_t i; - int n_cols =7; - size_t n_rows = cmd->n_vars * 3 + 1; - - struct tab_table *t = tab_create (n_cols, n_rows); - - tab_headers (t, 2, 0, 1, 0); + struct pivot_table *table = pivot_table_create (N_("ANOVA")); - tab_box (t, - TAL_2, TAL_2, - -1, TAL_1, - 0, 0, - n_cols - 1, n_rows - 1); + pivot_dimension_create (table, PIVOT_AXIS_COLUMN, N_("Statistics"), + N_("Sum of Squares"), PIVOT_RC_OTHER, + N_("df"), PIVOT_RC_INTEGER, + N_("Mean Square"), PIVOT_RC_OTHER, + N_("F"), PIVOT_RC_OTHER, + N_("Sig."), PIVOT_RC_SIGNIFICANCE); - tab_hline (t, TAL_2, 0, n_cols - 1, 1 ); - tab_vline (t, TAL_2, 2, 0, n_rows - 1); - tab_vline (t, TAL_0, 1, 0, 0); + pivot_dimension_create (table, PIVOT_AXIS_ROW, N_("Type"), + N_("Between Groups"), N_("Within Groups"), + N_("Total")); - tab_text (t, 2, 0, TAB_CENTER | TAT_TITLE, _("Sum of Squares")); - tab_text (t, 3, 0, TAB_CENTER | TAT_TITLE, _("df")); - tab_text (t, 4, 0, TAB_CENTER | TAT_TITLE, _("Mean Square")); - tab_text (t, 5, 0, TAB_CENTER | TAT_TITLE, _("F")); - tab_text (t, 6, 0, TAB_CENTER | TAT_TITLE, _("Significance")); + struct pivot_dimension *variables = pivot_dimension_create ( + table, PIVOT_AXIS_ROW, N_("Variables")); - - for (i = 0; i < cmd->n_vars; ++i) + for (size_t i = 0; i < cmd->n_vars; ++i) { - double n; - double df1, df2; - double msa; - const char *s = var_to_string (cmd->vars[i]); + int var_idx = pivot_category_create_leaf ( + variables->root, pivot_value_new_variable (cmd->vars[i])); + const struct per_var_ws *pvw = &ws->vws[i]; + double n; moments1_calculate (ws->dd_total[i]->mom, &n, NULL, NULL, NULL, NULL); - df1 = pvw->n_groups - 1; - df2 = n - pvw->n_groups; - msa = pvw->ssa / df1; - - tab_text (t, 0, i * 3 + 1, TAB_LEFT | TAT_TITLE, s); - tab_text (t, 1, i * 3 + 1, TAB_LEFT | TAT_TITLE, _("Between Groups")); - tab_text (t, 1, i * 3 + 2, TAB_LEFT | TAT_TITLE, _("Within Groups")); - tab_text (t, 1, i * 3 + 3, TAB_LEFT | TAT_TITLE, _("Total")); - - if (i > 0) - tab_hline (t, TAL_1, 0, n_cols - 1, i * 3 + 1); - - - /* Sums of Squares */ - tab_double (t, 2, i * 3 + 1, 0, pvw->ssa, NULL); - tab_double (t, 2, i * 3 + 3, 0, pvw->sst, NULL); - tab_double (t, 2, i * 3 + 2, 0, pvw->sse, NULL); - + double df1 = pvw->n_groups - 1; + double df2 = n - pvw->n_groups; + double msa = pvw->ssa / df1; + double F = msa / pvw->mse ; - /* Degrees of freedom */ - tab_fixed (t, 3, i * 3 + 1, 0, df1, 4, 0); - tab_fixed (t, 3, i * 3 + 2, 0, df2, 4, 0); - tab_fixed (t, 3, i * 3 + 3, 0, n - 1, 4, 0); - - /* Mean Squares */ - tab_double (t, 4, i * 3 + 1, TAB_RIGHT, msa, NULL); - tab_double (t, 4, i * 3 + 2, TAB_RIGHT, pvw->mse, NULL); - - { - const double F = msa / pvw->mse ; - - /* The F value */ - tab_double (t, 5, i * 3 + 1, 0, F, NULL); - - /* The significance */ - tab_double (t, 6, i * 3 + 1, 0, gsl_cdf_fdist_Q (F, df1, df2), NULL); - } + struct entry + { + int stat_idx; + int type_idx; + double x; + } + entries[] = { + /* Sums of Squares. */ + { 0, 0, pvw->ssa }, + { 0, 1, pvw->sse }, + { 0, 2, pvw->sst }, + /* Degrees of Freedom. */ + { 1, 0, df1 }, + { 1, 1, df2 }, + { 1, 2, n - 1 }, + /* Mean Squares. */ + { 2, 0, msa }, + { 2, 1, pvw->mse }, + /* F. */ + { 3, 0, F }, + /* Significance. */ + { 4, 0, gsl_cdf_fdist_Q (F, df1, df2) }, + }; + for (size_t j = 0; j < sizeof entries / sizeof *entries; j++) + { + const struct entry *e = &entries[j]; + pivot_table_put3 (table, e->stat_idx, e->type_idx, var_idx, + pivot_value_new_number (e->x)); + } } - tab_title (t, _("ANOVA")); - tab_submit (t); + pivot_table_submit (table); } - /* Show the descriptives table */ static void show_descriptives (const struct oneway_spec *cmd, const struct oneway_workspace *ws) { - size_t v; - int n_cols = 10; - struct tab_table *t; - int row; - - const double confidence = 0.95; - const double q = (1.0 - confidence) / 2.0; - - const struct fmt_spec *wfmt = cmd->wv ? var_get_print_format (cmd->wv) : &F_8_0; - - int n_rows = 2; - - for (v = 0; v < cmd->n_vars; ++v) - n_rows += ws->actual_number_of_groups + 1; - - t = tab_create (n_cols, n_rows); - tab_headers (t, 2, 0, 2, 0); - - /* Put a frame around the entire box, and vertical lines inside */ - tab_box (t, - TAL_2, TAL_2, - -1, TAL_1, - 0, 0, - n_cols - 1, n_rows - 1); - - /* Underline headers */ - tab_hline (t, TAL_2, 0, n_cols - 1, 2); - tab_vline (t, TAL_2, 2, 0, n_rows - 1); - - tab_text (t, 2, 1, TAB_CENTER | TAT_TITLE, _("N")); - tab_text (t, 3, 1, TAB_CENTER | TAT_TITLE, _("Mean")); - tab_text (t, 4, 1, TAB_CENTER | TAT_TITLE, _("Std. Deviation")); - tab_text (t, 5, 1, TAB_CENTER | TAT_TITLE, _("Std. Error")); - - - tab_vline (t, TAL_0, 7, 0, 0); - tab_hline (t, TAL_1, 6, 7, 1); - tab_joint_text_format (t, 6, 0, 7, 0, TAB_CENTER | TAT_TITLE, - _("%g%% Confidence Interval for Mean"), - confidence*100.0); + if (!cmd->n_vars) + return; + const struct categoricals *cats = covariance_get_categoricals ( + ws->vws[0].cov); - tab_text (t, 6, 1, TAB_CENTER | TAT_TITLE, _("Lower Bound")); - tab_text (t, 7, 1, TAB_CENTER | TAT_TITLE, _("Upper Bound")); + struct pivot_table *table = pivot_table_create (N_("Descriptives")); + pivot_table_set_weight_format (table, cmd->wfmt); - tab_text (t, 8, 1, TAB_CENTER | TAT_TITLE, _("Minimum")); - tab_text (t, 9, 1, TAB_CENTER | TAT_TITLE, _("Maximum")); + const double confidence = 0.95; - tab_title (t, _("Descriptives")); + struct pivot_dimension *statistics = pivot_dimension_create ( + table, PIVOT_AXIS_COLUMN, N_("Statistics"), + N_("N"), PIVOT_RC_COUNT, N_("Mean"), N_("Std. Deviation"), + N_("Std. Error")); + struct pivot_category *interval = pivot_category_create_group__ ( + statistics->root, + pivot_value_new_text_format (N_("%g%% Confidence Interval for Mean"), + confidence * 100.0)); + pivot_category_create_leaves (interval, N_("Lower Bound"), + N_("Upper Bound")); + pivot_category_create_leaves (statistics->root, + N_("Minimum"), N_("Maximum")); + + struct pivot_dimension *indep_var = pivot_dimension_create__ ( + table, PIVOT_AXIS_ROW, pivot_value_new_variable (cmd->indep_var)); + indep_var->root->show_label = true; + size_t n; + union value *values = categoricals_get_var_values (cats, cmd->indep_var, &n); + for (size_t j = 0; j < n; j++) + pivot_category_create_leaf ( + indep_var->root, pivot_value_new_var_value (cmd->indep_var, &values[j])); + pivot_category_create_leaf ( + indep_var->root, pivot_value_new_text_format (N_("Total"))); + + struct pivot_dimension *dep_var = pivot_dimension_create ( + table, PIVOT_AXIS_ROW, N_("Dependent Variable")); - row = 2; - for (v = 0; v < cmd->n_vars; ++v) + const double q = (1.0 - confidence) / 2.0; + for (int v = 0; v < cmd->n_vars; ++v) { - const char *s = var_to_string (cmd->vars[v]); - const struct fmt_spec *fmt = var_get_print_format (cmd->vars[v]); - - int count = 0; + int dep_var_idx = pivot_category_create_leaf ( + dep_var->root, pivot_value_new_variable (cmd->vars[v])); struct per_var_ws *pvw = &ws->vws[v]; const struct categoricals *cats = covariance_get_categoricals (pvw->cov); - tab_text (t, 0, row, TAB_LEFT | TAT_TITLE, s); - if ( v > 0) - tab_hline (t, TAL_1, 0, n_cols - 1, row); - - for (count = 0; count < categoricals_total (cats); ++count) + int count; + for (count = 0; count < categoricals_n_total (cats); ++count) { - double T; - double n, mean, variance; - double std_dev, std_error ; - - struct string vstr; - - const union value *gval = categoricals_get_value_by_subscript (cats, count); - const struct descriptive_data *dd = categoricals_get_user_data_by_subscript (cats, count); + const struct descriptive_data *dd + = categoricals_get_user_data_by_category (cats, count); + double n, mean, variance; moments1_calculate (dd->mom, &n, &mean, &variance, NULL, NULL); - std_dev = sqrt (variance); - std_error = std_dev / sqrt (n) ; - - ds_init_empty (&vstr); - - var_append_value_name (cmd->indep_var, gval, &vstr); - - tab_text (t, 1, row + count, - TAB_LEFT | TAT_TITLE, - ds_cstr (&vstr)); - - ds_destroy (&vstr); - - /* Now fill in the numbers ... */ - - tab_double (t, 2, row + count, 0, n, wfmt); - - tab_double (t, 3, row + count, 0, mean, NULL); - - tab_double (t, 4, row + count, 0, std_dev, NULL); - - - tab_double (t, 5, row + count, 0, std_error, NULL); - - /* Now the confidence interval */ - - T = gsl_cdf_tdist_Qinv (q, n - 1); - - tab_double (t, 6, row + count, 0, - mean - T * std_error, NULL); - - tab_double (t, 7, row + count, 0, - mean + T * std_error, NULL); - - /* Min and Max */ - - tab_double (t, 8, row + count, 0, dd->minimum, fmt); - tab_double (t, 9, row + count, 0, dd->maximum, fmt); + double std_dev = sqrt (variance); + double std_error = std_dev / sqrt (n) ; + double T = gsl_cdf_tdist_Qinv (q, n - 1); + + double entries[] = { + n, + mean, + std_dev, + std_error, + mean - T * std_error, + mean + T * std_error, + dd->minimum, + dd->maximum, + }; + for (size_t i = 0; i < sizeof entries / sizeof *entries; i++) + pivot_table_put3 (table, i, count, dep_var_idx, + pivot_value_new_number (entries[i])); } - { - double T; - double n, mean, variance; - double std_dev; - double std_error; - - moments1_calculate (ws->dd_total[v]->mom, &n, &mean, &variance, NULL, NULL); - - std_dev = sqrt (variance); - std_error = std_dev / sqrt (n) ; - - tab_text (t, 1, row + count, - TAB_LEFT | TAT_TITLE, _("Total")); - - tab_double (t, 2, row + count, 0, n, wfmt); - - tab_double (t, 3, row + count, 0, mean, NULL); - - tab_double (t, 4, row + count, 0, std_dev, NULL); - - tab_double (t, 5, row + count, 0, std_error, NULL); - - /* Now the confidence interval */ - T = gsl_cdf_tdist_Qinv (q, n - 1); - - tab_double (t, 6, row + count, 0, - mean - T * std_error, NULL); - - tab_double (t, 7, row + count, 0, - mean + T * std_error, NULL); - - /* Min and Max */ - tab_double (t, 8, row + count, 0, ws->dd_total[v]->minimum, fmt); - tab_double (t, 9, row + count, 0, ws->dd_total[v]->maximum, fmt); - } - - row += categoricals_total (cats) + 1; + if (categoricals_is_complete (cats)) + { + double n, mean, variance; + moments1_calculate (ws->dd_total[v]->mom, &n, &mean, &variance, + NULL, NULL); + + double std_dev = sqrt (variance); + double std_error = std_dev / sqrt (n) ; + double T = gsl_cdf_tdist_Qinv (q, n - 1); + + double entries[] = { + n, + mean, + std_dev, + std_error, + mean - T * std_error, + mean + T * std_error, + ws->dd_total[v]->minimum, + ws->dd_total[v]->maximum, + }; + for (size_t i = 0; i < sizeof entries / sizeof *entries; i++) + pivot_table_put3 (table, i, count, dep_var_idx, + pivot_value_new_number (entries[i])); + } } - tab_submit (t); + pivot_table_submit (table); } /* Show the homogeneity table */ static void show_homogeneity (const struct oneway_spec *cmd, const struct oneway_workspace *ws) { - size_t v; - int n_cols = 5; - size_t n_rows = cmd->n_vars + 1; - - struct tab_table *t = tab_create (n_cols, n_rows); - tab_headers (t, 1, 0, 1, 0); - - /* Put a frame around the entire box, and vertical lines inside */ - tab_box (t, - TAL_2, TAL_2, - -1, TAL_1, - 0, 0, - n_cols - 1, n_rows - 1); - + struct pivot_table *table = pivot_table_create ( + N_("Test of Homogeneity of Variances")); - tab_hline (t, TAL_2, 0, n_cols - 1, 1); - tab_vline (t, TAL_2, 1, 0, n_rows - 1); + pivot_dimension_create (table, PIVOT_AXIS_COLUMN, N_("Statistics"), + N_("Levene Statistic"), PIVOT_RC_OTHER, + N_("df1"), PIVOT_RC_INTEGER, + N_("df2"), PIVOT_RC_INTEGER, + N_("Sig."), PIVOT_RC_SIGNIFICANCE); - tab_text (t, 1, 0, TAB_CENTER | TAT_TITLE, _("Levene Statistic")); - tab_text (t, 2, 0, TAB_CENTER | TAT_TITLE, _("df1")); - tab_text (t, 3, 0, TAB_CENTER | TAT_TITLE, _("df2")); - tab_text (t, 4, 0, TAB_CENTER | TAT_TITLE, _("Significance")); + struct pivot_dimension *variables = pivot_dimension_create ( + table, PIVOT_AXIS_ROW, N_("Variables")); - tab_title (t, _("Test of Homogeneity of Variances")); - - for (v = 0; v < cmd->n_vars; ++v) + for (int v = 0; v < cmd->n_vars; ++v) { - double n; - const struct per_var_ws *pvw = &ws->vws[v]; - double F = pvw->levene_w; - - const struct variable *var = cmd->vars[v]; - const char *s = var_to_string (var); - double df1, df2; + int var_idx = pivot_category_create_leaf ( + variables->root, pivot_value_new_variable (cmd->vars[v])); + double n; moments1_calculate (ws->dd_total[v]->mom, &n, NULL, NULL, NULL, NULL); - df1 = pvw->n_groups - 1; - df2 = n - pvw->n_groups; - - tab_text (t, 0, v + 1, TAB_LEFT | TAT_TITLE, s); - - tab_double (t, 1, v + 1, TAB_RIGHT, F, NULL); - tab_fixed (t, 2, v + 1, TAB_RIGHT, df1, 8, 0); - tab_fixed (t, 3, v + 1, TAB_RIGHT, df2, 8, 0); + const struct per_var_ws *pvw = &ws->vws[v]; + double df1 = pvw->n_groups - 1; + double df2 = n - pvw->n_groups; + double F = levene_calculate (pvw->nl); - /* Now the significance */ - tab_double (t, 4, v + 1, TAB_RIGHT, gsl_cdf_fdist_Q (F, df1, df2), NULL); + double entries[] = + { + F, + df1, + df2, + gsl_cdf_fdist_Q (F, df1, df2), + }; + for (size_t i = 0; i < sizeof entries / sizeof *entries; i++) + pivot_table_put2 (table, i, var_idx, + pivot_value_new_number (entries[i])); } - tab_submit (t); + pivot_table_submit (table); } @@ -881,158 +1190,87 @@ show_homogeneity (const struct oneway_spec *cmd, const struct oneway_workspace * static void show_contrast_coeffs (const struct oneway_spec *cmd, const struct oneway_workspace *ws) { - int c_num = 0; - struct ll *cli; - - int n_contrasts = ll_count (&cmd->contrast_list); - int n_cols = 2 + ws->actual_number_of_groups; - int n_rows = 2 + n_contrasts; + struct pivot_table *table = pivot_table_create (N_("Contrast Coefficients")); - struct tab_table *t; + struct pivot_dimension *indep_var = pivot_dimension_create__ ( + table, PIVOT_AXIS_COLUMN, pivot_value_new_variable (cmd->indep_var)); + indep_var->root->show_label = true; - const struct covariance *cov = ws->vws[0].cov ; + struct pivot_dimension *contrast = pivot_dimension_create ( + table, PIVOT_AXIS_ROW, N_("Contrast")); + contrast->root->show_label = true; - t = tab_create (n_cols, n_rows); - tab_headers (t, 2, 0, 2, 0); + const struct covariance *cov = ws->vws[0].cov; - /* Put a frame around the entire box, and vertical lines inside */ - tab_box (t, - TAL_2, TAL_2, - -1, TAL_1, - 0, 0, - n_cols - 1, n_rows - 1); - - tab_box (t, - -1, -1, - TAL_0, TAL_0, - 2, 0, - n_cols - 1, 0); - - tab_box (t, - -1, -1, - TAL_0, TAL_0, - 0, 0, - 1, 1); - - tab_hline (t, TAL_1, 2, n_cols - 1, 1); - tab_hline (t, TAL_2, 0, n_cols - 1, 2); - - tab_vline (t, TAL_2, 2, 0, n_rows - 1); - - tab_title (t, _("Contrast Coefficients")); - - tab_text (t, 0, 2, TAB_LEFT | TAT_TITLE, _("Contrast")); - - - tab_joint_text (t, 2, 0, n_cols - 1, 0, TAB_CENTER | TAT_TITLE, - var_to_string (cmd->indep_var)); - - for ( cli = ll_head (&cmd->contrast_list); - cli != ll_null (&cmd->contrast_list); - cli = ll_next (cli)) + const struct contrasts_node *cn; + int c_num = 1; + ll_for_each (cn, struct contrasts_node, ll, &cmd->contrast_list) { - int count = 0; - struct contrasts_node *cn = ll_data (cli, struct contrasts_node, ll); - struct ll *coeffi ; - - tab_text_format (t, 1, c_num + 2, TAB_CENTER, "%d", c_num + 1); + int contrast_idx = pivot_category_create_leaf ( + contrast->root, pivot_value_new_integer (c_num++)); - for (coeffi = ll_head (&cn->coefficient_list); - coeffi != ll_null (&cn->coefficient_list); - ++count, coeffi = ll_next (coeffi)) + const struct coeff_node *coeffn; + int indep_idx = 0; + ll_for_each (coeffn, struct coeff_node, ll, &cn->coefficient_list) { const struct categoricals *cats = covariance_get_categoricals (cov); - const union value *val = categoricals_get_value_by_subscript (cats, count); - struct string vstr; - - ds_init_empty (&vstr); - - var_append_value_name (cmd->indep_var, val, &vstr); - - tab_text (t, count + 2, 1, TAB_CENTER | TAT_TITLE, ds_cstr (&vstr)); + const struct ccase *gcc = categoricals_get_case_by_category ( + cats, indep_idx); - ds_destroy (&vstr); + if (!contrast_idx) + pivot_category_create_leaf ( + indep_var->root, pivot_value_new_var_value ( + cmd->indep_var, case_data (gcc, cmd->indep_var))); - if (cn->bad_count) - tab_text (t, count + 2, c_num + 2, TAB_RIGHT, "?" ); - else - { - struct coeff_node *coeffn = ll_data (coeffi, struct coeff_node, ll); - - tab_text_format (t, count + 2, c_num + 2, TAB_RIGHT, "%g", coeffn->coeff); - } + pivot_table_put2 (table, indep_idx++, contrast_idx, + pivot_value_new_integer (coeffn->coeff)); } - ++c_num; } - tab_submit (t); + pivot_table_submit (table); } - /* Show the results of the contrast tests */ static void show_contrast_tests (const struct oneway_spec *cmd, const struct oneway_workspace *ws) { + struct pivot_table *table = pivot_table_create (N_("Contrast Tests")); + + pivot_dimension_create (table, PIVOT_AXIS_COLUMN, N_("Statistics"), + N_("Value of Contrast"), PIVOT_RC_OTHER, + N_("Std. Error"), PIVOT_RC_OTHER, + N_("t"), PIVOT_RC_OTHER, + N_("df"), PIVOT_RC_OTHER, + N_("Sig. (2-tailed)"), PIVOT_RC_SIGNIFICANCE); + + struct pivot_dimension *contrasts = pivot_dimension_create ( + table, PIVOT_AXIS_ROW, N_("Contrast")); + contrasts->root->show_label = true; int n_contrasts = ll_count (&cmd->contrast_list); - size_t v; - int n_cols = 8; - size_t n_rows = 1 + cmd->n_vars * 2 * n_contrasts; - - struct tab_table *t; - - t = tab_create (n_cols, n_rows); - tab_headers (t, 3, 0, 1, 0); + for (int i = 1; i <= n_contrasts; i++) + pivot_category_create_leaf (contrasts->root, pivot_value_new_integer (i)); - /* Put a frame around the entire box, and vertical lines inside */ - tab_box (t, - TAL_2, TAL_2, - -1, TAL_1, - 0, 0, - n_cols - 1, n_rows - 1); + pivot_dimension_create (table, PIVOT_AXIS_ROW, N_("Assumption"), + N_("Assume equal variances"), + N_("Does not assume equal variances")); - tab_box (t, - -1, -1, - TAL_0, TAL_0, - 0, 0, - 2, 0); + struct pivot_dimension *variables = pivot_dimension_create ( + table, PIVOT_AXIS_ROW, N_("Dependent Variable")); - tab_hline (t, TAL_2, 0, n_cols - 1, 1); - tab_vline (t, TAL_2, 3, 0, n_rows - 1); - - tab_title (t, _("Contrast Tests")); - - tab_text (t, 2, 0, TAB_CENTER | TAT_TITLE, _("Contrast")); - tab_text (t, 3, 0, TAB_CENTER | TAT_TITLE, _("Value of Contrast")); - tab_text (t, 4, 0, TAB_CENTER | TAT_TITLE, _("Std. Error")); - tab_text (t, 5, 0, TAB_CENTER | TAT_TITLE, _("t")); - tab_text (t, 6, 0, TAB_CENTER | TAT_TITLE, _("df")); - tab_text (t, 7, 0, TAB_CENTER | TAT_TITLE, _("Sig. (2-tailed)")); - - for (v = 0; v < cmd->n_vars; ++v) + for (int v = 0; v < cmd->n_vars; ++v) { const struct per_var_ws *pvw = &ws->vws[v]; const struct categoricals *cats = covariance_get_categoricals (pvw->cov); - struct ll *cli; - int i = 0; - int lines_per_variable = 2 * n_contrasts; + if (!categoricals_is_complete (cats)) + continue; - tab_text (t, 0, (v * lines_per_variable) + 1, TAB_LEFT | TAT_TITLE, - var_to_string (cmd->vars[v])); + int var_idx = pivot_category_create_leaf ( + variables->root, pivot_value_new_variable (cmd->vars[v])); - for ( cli = ll_head (&cmd->contrast_list); - cli != ll_null (&cmd->contrast_list); - ++i, cli = ll_next (cli)) + struct contrasts_node *cn; + int contrast_idx = 0; + ll_for_each (cn, struct contrasts_node, ll, &cmd->contrast_list) { - struct contrasts_node *cn = ll_data (cli, struct contrasts_node, ll); - struct ll *coeffi ; - int ci = 0; - double contrast_value = 0.0; - double coef_msq = 0.0; - - double T; - double std_error_contrast; - double df; - double sec_vneq = 0.0; /* Note: The calculation of the degrees of freedom in the "variances not equal" case is painfull!! @@ -1045,129 +1283,172 @@ show_contrast_tests (const struct oneway_spec *cmd, const struct oneway_workspac } */ - double df_denominator = 0.0; - double df_numerator = 0.0; - double grand_n; - moments1_calculate (ws->dd_total[v]->mom, &grand_n, NULL, NULL, NULL, NULL); - df = grand_n - pvw->n_groups; + moments1_calculate (ws->dd_total[v]->mom, &grand_n, NULL, NULL, + NULL, NULL); + double df = grand_n - pvw->n_groups; - if ( i == 0 ) + double contrast_value = 0.0; + double coef_msq = 0.0; + double sec_vneq = 0.0; + double df_denominator = 0.0; + double df_numerator = 0.0; + struct coeff_node *coeffn; + int ci = 0; + ll_for_each (coeffn, struct coeff_node, ll, &cn->coefficient_list) { - tab_text (t, 1, (v * lines_per_variable) + i + 1, - TAB_LEFT | TAT_TITLE, - _("Assume equal variances")); + const struct descriptive_data *dd + = categoricals_get_user_data_by_category (cats, ci); + const double coef = coeffn->coeff; - tab_text (t, 1, (v * lines_per_variable) + i + 1 + n_contrasts, - TAB_LEFT | TAT_TITLE, - _("Does not assume equal")); - } - - tab_text_format (t, 2, (v * lines_per_variable) + i + 1, - TAB_CENTER | TAT_TITLE, "%d", i + 1); - - - tab_text_format (t, 2, - (v * lines_per_variable) + i + 1 + n_contrasts, - TAB_CENTER | TAT_TITLE, "%d", i + 1); - - if (cn->bad_count) - continue; - - for (coeffi = ll_head (&cn->coefficient_list); - coeffi != ll_null (&cn->coefficient_list); - ++ci, coeffi = ll_next (coeffi)) - { double n, mean, variance; - const struct descriptive_data *dd = categoricals_get_user_data_by_subscript (cats, ci); - struct coeff_node *cn = ll_data (coeffi, struct coeff_node, ll); - const double coef = cn->coeff; - double winv ; - moments1_calculate (dd->mom, &n, &mean, &variance, NULL, NULL); - winv = variance / n; - + double winv = variance / n; contrast_value += coef * mean; + coef_msq += pow2 (coef) / n; + sec_vneq += pow2 (coef) * variance / n; + df_numerator += pow2 (coef) * winv; + df_denominator += pow2(pow2 (coef) * winv) / (n - 1); - coef_msq += (pow2 (coef)) / n; - - sec_vneq += (pow2 (coef)) * variance / n; - - df_numerator += (pow2 (coef)) * winv; - df_denominator += pow2((pow2 (coef)) * winv) / (n - 1); + ci++; } - sec_vneq = sqrt (sec_vneq); - df_numerator = pow2 (df_numerator); - tab_double (t, 3, (v * lines_per_variable) + i + 1, - TAB_RIGHT, contrast_value, NULL); - - tab_double (t, 3, (v * lines_per_variable) + i + 1 + - n_contrasts, - TAB_RIGHT, contrast_value, NULL); - - std_error_contrast = sqrt (pvw->mse * coef_msq); - - /* Std. Error */ - tab_double (t, 4, (v * lines_per_variable) + i + 1, - TAB_RIGHT, std_error_contrast, - NULL); - - T = fabs (contrast_value / std_error_contrast); - - /* T Statistic */ - - tab_double (t, 5, (v * lines_per_variable) + i + 1, - TAB_RIGHT, T, - NULL); + double std_error_contrast = sqrt (pvw->mse * coef_msq); + double T = contrast_value / std_error_contrast; + double T_ne = contrast_value / sec_vneq; + double df_ne = df_numerator / df_denominator; + struct entry + { + int stat_idx; + int assumption_idx; + double x; + } + entries[] = + { + /* Assume equal. */ + { 0, 0, contrast_value }, + { 1, 0, std_error_contrast }, + { 2, 0, T }, + { 3, 0, df }, + { 4, 0, 2 * gsl_cdf_tdist_Q (fabs(T), df) }, + /* Do not assume equal. */ + { 0, 1, contrast_value }, + { 1, 1, sec_vneq }, + { 2, 1, T_ne }, + { 3, 1, df_ne }, + { 4, 1, 2 * gsl_cdf_tdist_Q (fabs(T_ne), df_ne) }, + }; + + for (size_t i = 0; i < sizeof entries / sizeof *entries; i++) + { + const struct entry *e = &entries[i]; + pivot_table_put4 ( + table, e->stat_idx, contrast_idx, e->assumption_idx, var_idx, + pivot_value_new_number (e->x)); + } - /* Degrees of Freedom */ - tab_fixed (t, 6, (v * lines_per_variable) + i + 1, - TAB_RIGHT, df, - 8, 0); + contrast_idx++; + } + } + pivot_table_submit (table); +} - /* Significance TWO TAILED !!*/ - tab_double (t, 7, (v * lines_per_variable) + i + 1, - TAB_RIGHT, 2 * gsl_cdf_tdist_Q (T, df), - NULL); +static void +show_comparisons (const struct oneway_spec *cmd, const struct oneway_workspace *ws, int v) +{ + struct pivot_table *table = pivot_table_create__ ( + pivot_value_new_user_text_nocopy (xasprintf ( + _("Multiple Comparisons (%s)"), + var_to_string (cmd->vars[v]))), + "Multiple Comparisons"); + + struct pivot_dimension *statistics = pivot_dimension_create ( + table, PIVOT_AXIS_COLUMN, N_("Statistics"), + N_("Mean Difference (I - J)"), PIVOT_RC_OTHER, + N_("Std. Error"), PIVOT_RC_OTHER, + N_("Sig."), PIVOT_RC_SIGNIFICANCE); + struct pivot_category *interval = pivot_category_create_group__ ( + statistics->root, + pivot_value_new_text_format (N_("%g%% Confidence Interval"), + (1 - cmd->alpha) * 100.0)); + pivot_category_create_leaves (interval, + N_("Lower Bound"), PIVOT_RC_OTHER, + N_("Upper Bound"), PIVOT_RC_OTHER); + + struct pivot_dimension *j_family = pivot_dimension_create ( + table, PIVOT_AXIS_ROW, N_("(J) Family")); + j_family->root->show_label = true; + + struct pivot_dimension *i_family = pivot_dimension_create ( + table, PIVOT_AXIS_ROW, N_("(J) Family")); + i_family->root->show_label = true; + + const struct per_var_ws *pvw = &ws->vws[v]; + const struct categoricals *cat = pvw->cat; + for (int i = 0; i < pvw->n_groups; i++) + { + const struct ccase *gcc = categoricals_get_case_by_category (cat, i); + for (int j = 0; j < 2; j++) + pivot_category_create_leaf ( + j ? j_family->root : i_family->root, + pivot_value_new_var_value (cmd->indep_var, + case_data (gcc, cmd->indep_var))); + } - /* Now for the Variances NOT Equal case */ + struct pivot_dimension *test = pivot_dimension_create ( + table, PIVOT_AXIS_ROW, N_("Test")); - /* Std. Error */ - tab_double (t, 4, - (v * lines_per_variable) + i + 1 + n_contrasts, - TAB_RIGHT, sec_vneq, - NULL); + for (int p = 0; p < cmd->n_posthoc; ++p) + { + const struct posthoc *ph = &ph_tests[cmd->posthoc[p]]; - T = contrast_value / sec_vneq; - tab_double (t, 5, - (v * lines_per_variable) + i + 1 + n_contrasts, - TAB_RIGHT, T, - NULL); + int test_idx = pivot_category_create_leaf ( + test->root, pivot_value_new_text (ph->label)); - df = df_numerator / df_denominator; + for (int i = 0; i < pvw->n_groups ; ++i) + { + struct descriptive_data *dd_i + = categoricals_get_user_data_by_category (cat, i); + double weight_i, mean_i, var_i; + moments1_calculate (dd_i->mom, &weight_i, &mean_i, &var_i, 0, 0); - tab_double (t, 6, - (v * lines_per_variable) + i + 1 + n_contrasts, - TAB_RIGHT, df, - NULL); + for (int j = 0 ; j < pvw->n_groups; ++j) + { + if (j == i) + continue; - /* The Significance */ - tab_double (t, 7, (v * lines_per_variable) + i + 1 + n_contrasts, - TAB_RIGHT, 2 * gsl_cdf_tdist_Q (T,df), - NULL); + struct descriptive_data *dd_j + = categoricals_get_user_data_by_category (cat, j); + double weight_j, mean_j, var_j; + moments1_calculate (dd_j->mom, &weight_j, &mean_j, &var_j, 0, 0); + + double std_err = pvw->mse; + std_err *= weight_i + weight_j; + std_err /= weight_i * weight_j; + std_err = sqrt (std_err); + + double sig = 2 * multiple_comparison_sig (std_err, pvw, + dd_i, dd_j, ph); + double half_range = mc_half_range (cmd, pvw, std_err, + dd_i, dd_j, ph); + double entries[] = { + mean_i - mean_j, + std_err, + sig, + (mean_i - mean_j) - half_range, + (mean_i - mean_j) + half_range, + }; + for (size_t k = 0; k < sizeof entries / sizeof *entries; k++) + pivot_table_put4 (table, k, j, i, test_idx, + pivot_value_new_number (entries[k])); + } } - - if ( v > 0 ) - tab_hline (t, TAL_1, 0, n_cols - 1, (v * lines_per_variable) + 1); } - tab_submit (t); + pivot_table_submit (table); } - -