+++ /dev/null
-/* PSPP - a program for statistical analysis.
- 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
- the Free Software Foundation, either version 3 of the License, or
- (at your option) any later version.
-
- This program is distributed in the hope that it will be useful,
- but WITHOUT ANY WARRANTY; without even the implied warranty of
- MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
- GNU General Public License for more details.
-
- You should have received a copy of the GNU General Public License
- along with this program. If not, see <http://www.gnu.org/licenses/>. */
-
-#include <config.h>
-
-#include <float.h>
-#include <gsl/gsl_cdf.h>
-#include <gsl/gsl_matrix.h>
-#include <math.h>
-
-#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 "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;
-
- double n;
-
- double sst;
- double sse;
- double ssa;
-
- int n_groups;
-
- double mse;
- };
-
-/* Per category data */
-struct descriptive_data
- {
- const struct variable *var;
- struct moments1 *mom;
-
- double minimum;
- double maximum;
- };
-
-enum missing_type
- {
- MISS_LISTWISE,
- MISS_ANALYSIS,
- };
-
-struct coeff_node
-{
- struct ll ll;
- double coeff;
-};
-
-
-struct contrasts_node
-{
- 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;
-
- pinv_func *pinv;
-};
-
-struct oneway_spec
-{
- size_t n_vars;
- const struct variable **vars;
-
- const struct variable *indep_var;
-
- bool descriptive_stats;
- bool homogeneity_stats;
-
- enum missing_type missing_type;
- enum mv_class exclude;
-
- /* List of contrasts */
- struct ll_list contrast_list;
-
- /* 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;
-};
-
-static double
-df_common (const struct per_var_ws *pvw, const struct moments1 *mom_i UNUSED, const struct moments1 *mom_j UNUSED)
-{
- return pvw->n - pvw->n_groups;
-}
-
-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;
-
- 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)
-{
- return std_err * gsl_cdf_tdist_Pinv (1.0 - alpha / 2.0, df);
-}
-
-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);
-}
-
-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}
- };
-
-
-struct oneway_workspace
-{
- /* The number of distinct values of the independent variable, when all
- missing values are disregarded */
- int actual_number_of_groups;
-
- struct per_var_ws *vws;
-
- /* An array of descriptive data. One for each dependent variable */
- struct descriptive_data **dd_total;
-};
-
-/* Routines to show the output tables */
-static void show_anova_table (const struct oneway_spec *, const struct oneway_workspace *);
-static void show_descriptives (const struct oneway_spec *, const struct oneway_workspace *);
-static void show_homogeneity (const struct oneway_spec *, const struct oneway_workspace *);
-
-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);
- struct oneway_spec oneway = {
- .missing_type = MISS_ANALYSIS,
- .exclude = MV_ANY,
- .wv = dict_get_weight (dict),
- .wfmt = dict_get_weight_format (dict),
- .alpha = 0.05,
- };
-
- ll_init (&oneway.contrast_list);
- if (lex_match (lexer, T_SLASH))
- {
- if (!lex_force_match_id (lexer, "VARIABLES"))
- goto error;
- lex_match (lexer, T_EQUALS);
- }
-
- if (!parse_variables_const (lexer, dict,
- &oneway.vars, &oneway.n_vars,
- PV_NO_DUPLICATE | PV_NUMERIC))
- goto error;
-
- 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)
- {
- lex_match (lexer, T_SLASH);
-
- if (lex_match_id (lexer, "STATISTICS"))
- {
- lex_match (lexer, T_EQUALS);
- while (lex_token (lexer) != T_ENDCMD && lex_token (lexer) != T_SLASH)
- {
- if (lex_match_id (lexer, "DESCRIPTIVES"))
- oneway.descriptive_stats = true;
- else if (lex_match_id (lexer, "HOMOGENEITY"))
- oneway.homogeneity_stats = true;
- else
- {
- lex_error_expecting (lexer, "DESCRIPTIVES", "HOMOGENEITY");
- goto error;
- }
- }
- }
- else if (lex_match_id (lexer, "POSTHOC"))
- {
- lex_match (lexer, T_EQUALS);
- while (lex_token (lexer) != T_ENDCMD && lex_token (lexer) != T_SLASH)
- {
- bool method = false;
- for (size_t p = 0; p < sizeof ph_tests / sizeof *ph_tests; ++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)
- || !lex_force_num (lexer))
- goto error;
- oneway.alpha = lex_number (lexer);
- lex_get (lexer);
- if (!lex_force_match (lexer, T_RPAREN))
- goto error;
- }
- else
- {
- lex_error (lexer, _("Unknown post hoc analysis method."));
- goto error;
- }
- }
- }
- }
- else if (lex_match_id (lexer, "CONTRAST"))
- {
- struct contrasts_node *cl = XZALLOC (struct contrasts_node);
-
- struct ll_list *coefficient_list = &cl->coefficient_list;
- lex_match (lexer, T_EQUALS);
-
- ll_init (coefficient_list);
-
- while (lex_token (lexer) != T_ENDCMD && lex_token (lexer) != T_SLASH)
- {
- if (!lex_force_num (lexer))
- {
- destroy_coeff_list (cl);
- goto error;
- }
-
- struct coeff_node *cc = xmalloc (sizeof *cc);
- cc->coeff = lex_number (lexer);
-
- ll_push_tail (coefficient_list, &cc->ll);
- lex_get (lexer);
- }
-
- 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"))
- {
- lex_match (lexer, T_EQUALS);
- while (lex_token (lexer) != T_ENDCMD && lex_token (lexer) != T_SLASH)
- {
- if (lex_match_id (lexer, "INCLUDE"))
- oneway.exclude = MV_SYSTEM;
- else if (lex_match_id (lexer, "EXCLUDE"))
- oneway.exclude = MV_ANY;
- else if (lex_match_id (lexer, "LISTWISE"))
- oneway.missing_type = MISS_LISTWISE;
- else if (lex_match_id (lexer, "ANALYSIS"))
- oneway.missing_type = MISS_ANALYSIS;
- else
- {
- lex_error_expecting (lexer, "INCLUDE", "EXCLUDE",
- "LISTWISE", "ANALYSIS");
- goto error;
- }
- }
- }
- else
- {
- lex_error_expecting (lexer, "STATISTICS", "POSTHOC", "CONTRAST",
- "MISSING");
- goto error;
- }
- }
-
- struct casegrouper *grouper = casegrouper_create_splits (proc_open (ds), dict);
- struct casereader *group;
- while (casegrouper_get_next_group (grouper, &group))
- run_oneway (&oneway, group, ds);
- bool ok = casegrouper_destroy (grouper);
- ok = proc_commit (ds) && ok;
-
- oneway_cleanup (&oneway);
- free (oneway.vars);
- return CMD_SUCCESS;
-
- error:
- oneway_cleanup (&oneway);
- free (oneway.vars);
- return CMD_FAILURE;
-}
-\f
-static struct descriptive_data *
-dd_create (const struct variable *var)
-{
- struct descriptive_data *dd = xmalloc (sizeof *dd);
-
- dd->mom = moments1_create (MOMENT_VARIANCE);
- dd->minimum = DBL_MAX;
- dd->maximum = -DBL_MAX;
- dd->var = var;
-
- return dd;
-}
-
-static void
-dd_destroy (struct descriptive_data *dd)
-{
- moments1_destroy (dd->mom);
- free (dd);
-}
-
-static void *
-makeit (const void *aux1, void *aux2 UNUSED)
-{
- const struct variable *var = aux1;
-
- struct descriptive_data *dd = dd_create (var);
-
- return dd;
-}
-
-static void
-killit (const void *aux1 UNUSED, void *aux2 UNUSED, void *user_data)
-{
- struct descriptive_data *dd = user_data;
-
- dd_destroy (dd);
-}
-
-
-static void
-updateit (const void *aux1, void *aux2, void *user_data,
- const struct ccase *c, double weight)
-{
- struct descriptive_data *dd = user_data;
-
- const struct variable *varp = aux1;
-
- const union value *valx = case_data (c, varp);
-
- struct descriptive_data *dd_total = aux2;
-
- moments1_add (dd->mom, valx->f, weight);
- if (valx->f < dd->minimum)
- dd->minimum = valx->f;
-
- if (valx->f > dd->maximum)
- dd->maximum = valx->f;
-
- {
- const struct variable *var = dd_total->var;
- const union value *val = case_data (c, var);
-
- moments1_add (dd_total->mom,
- val->f,
- weight);
-
- if (val->f < dd_total->minimum)
- dd_total->minimum = val->f;
-
- if (val->f > dd_total->maximum)
- dd_total->maximum = val->f;
- }
-}
-
-static void
-run_oneway (const struct oneway_spec *cmd, struct casereader *input,
- const struct dataset *ds)
-{
- struct dictionary *dict = dataset_dict (ds);
- struct oneway_workspace ws = {
- .vws = xcalloc (cmd->n_vars, sizeof *ws.vws),
- .dd_total = XCALLOC (cmd->n_vars, struct descriptive_data *),
- };
-
- for (size_t v = 0; v < cmd->n_vars; ++v)
- ws.dd_total[v] = dd_create (cmd->vars[v]);
-
- for (size_t v = 0; v < cmd->n_vars; ++v)
- {
- static const struct payload payload =
- {
- .create = makeit,
- .update = updateit,
- .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, true);
- ws.vws[v].nl = levene_create (var_get_width (cmd->indep_var), NULL);
- }
-
- output_split_file_values_peek (ds, input);
-
- struct taint *taint = taint_clone (casereader_get_taint (input));
- input = casereader_create_filter_missing (input, &cmd->indep_var, 1,
- cmd->exclude, NULL, NULL);
- if (cmd->missing_type == MISS_LISTWISE)
- input = casereader_create_filter_missing (input, cmd->vars, cmd->n_vars,
- cmd->exclude, NULL, NULL);
- input = casereader_create_filter_weight (input, dict, NULL, NULL);
-
- struct casereader *reader = casereader_clone (input);
- struct ccase *c;
- for (; (c = casereader_read (reader)) != NULL; case_unref (c))
- {
- double w = dict_get_case_weight (dict, c, NULL);
-
- for (size_t 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;
- }
-
- 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))
- {
- double w = dict_get_case_weight (dict, c, NULL);
- for (size_t 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;
- }
-
- 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))
- {
- double w = dict_get_case_weight (dict, c, NULL);
-
- for (size_t 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 (size_t v = 0; v < cmd->n_vars; ++v)
- {
- struct per_var_ws *pvw = &ws.vws[v];
-
- const struct categoricals *cats = covariance_get_categoricals (pvw->cov);
- if (!categoricals_sane (cats))
- {
- 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;
- }
-
- const gsl_matrix *ucm = covariance_calculate_unnormalized (pvw->cov);
-
- gsl_matrix *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_n_total (cats);
-
- pvw->mse = (pvw->sst - pvw->ssa) / (pvw->n - pvw->n_groups);
- }
-
- for (size_t v = 0; v < cmd->n_vars; ++v)
- {
- const struct categoricals *cats = covariance_get_categoricals (ws.vws[v].cov);
- if (categoricals_is_complete (cats))
- {
- if (categoricals_n_total (cats) > ws.actual_number_of_groups)
- ws.actual_number_of_groups = categoricals_n_total (cats);
- }
- }
- casereader_destroy (input);
-
- if (!taint_has_tainted_successor (taint))
- output_oneway (cmd, &ws);
-
- taint_destroy (taint);
-
- for (size_t 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 *, const struct oneway_workspace *);
-static void show_contrast_tests (const struct oneway_spec *, const struct oneway_workspace *);
-static void show_comparisons (const struct oneway_spec *, const struct oneway_workspace *, int depvar);
-
-static void
-output_oneway (const struct oneway_spec *cmd, struct oneway_workspace *ws)
-{
- size_t list_idx = 0;
-
- /* Check the sanity of the given contrast values */
- 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)
- {
- struct coeff_node *cn = NULL;
- double sum = 0;
- struct ll_list *cl = &coeff_list->coefficient_list;
- ++list_idx;
-
- if (ll_count (cl) != ws->actual_number_of_groups)
- {
- msg (SW,
- _("In contrast list %zu, the number of coefficients (%zu) does not equal the number of groups (%d). This contrast list will be ignored."),
- list_idx, 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)
- msg (SW, _("Coefficients for contrast %zu do not total zero"),
- list_idx);
- }
-
- if (cmd->descriptive_stats)
- show_descriptives (cmd, ws);
-
- if (cmd->homogeneity_stats)
- show_homogeneity (cmd, ws);
-
- show_anova_table (cmd, ws);
-
- if (ll_count (&cmd->contrast_list) > 0)
- {
- show_contrast_coeffs (cmd, ws);
- show_contrast_tests (cmd, ws);
- }
-
- if (cmd->posthoc)
- for (size_t 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);
- }
-}
-
-
-/* Show the ANOVA table */
-static void
-show_anova_table (const struct oneway_spec *cmd, const struct oneway_workspace *ws)
-{
- struct pivot_table *table = pivot_table_create (N_("ANOVA"));
-
- 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);
-
- pivot_dimension_create (table, PIVOT_AXIS_ROW, N_("Type"),
- N_("Between Groups"), N_("Within Groups"),
- N_("Total"));
-
- struct pivot_dimension *variables = pivot_dimension_create (
- table, PIVOT_AXIS_ROW, N_("Variables"));
-
- for (size_t i = 0; i < cmd->n_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);
-
- double df1 = pvw->n_groups - 1;
- double df2 = n - pvw->n_groups;
- double msa = pvw->ssa / df1;
- double F = msa / pvw->mse;
-
- 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));
- }
- }
-
- pivot_table_submit (table);
-}
-
-/* Show the descriptives table */
-static void
-show_descriptives (const struct oneway_spec *cmd, const struct oneway_workspace *ws)
-{
- if (!cmd->n_vars)
- return;
- const struct categoricals *cats = covariance_get_categoricals (
- ws->vws[0].cov);
-
- struct pivot_table *table = pivot_table_create (N_("Descriptives"));
- pivot_table_set_weight_format (table, cmd->wfmt);
-
- const double confidence = 0.95;
-
- 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"));
-
- const double q = (1.0 - confidence) / 2.0;
- for (int v = 0; v < cmd->n_vars; ++v)
- {
- 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);
-
- int count;
- for (count = 0; count < categoricals_n_total (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);
-
- 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]));
- }
-
- 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]));
- }
- }
-
- pivot_table_submit (table);
-}
-
-/* Show the homogeneity table */
-static void
-show_homogeneity (const struct oneway_spec *cmd, const struct oneway_workspace *ws)
-{
- struct pivot_table *table = pivot_table_create (
- N_("Test of Homogeneity of Variances"));
-
- 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);
-
- struct pivot_dimension *variables = pivot_dimension_create (
- table, PIVOT_AXIS_ROW, N_("Variables"));
-
- for (int v = 0; v < cmd->n_vars; ++v)
- {
- 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);
-
- 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);
-
- 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]));
- }
-
- pivot_table_submit (table);
-}
-
-
-/* Show the contrast coefficients table */
-static void
-show_contrast_coeffs (const struct oneway_spec *cmd, const struct oneway_workspace *ws)
-{
- struct pivot_table *table = pivot_table_create (N_("Contrast Coefficients"));
-
- 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;
-
- struct pivot_dimension *contrast = pivot_dimension_create (
- table, PIVOT_AXIS_ROW, N_("Contrast"));
- contrast->root->show_label = true;
-
- const struct covariance *cov = ws->vws[0].cov;
-
- const struct contrasts_node *cn;
- int c_num = 1;
- ll_for_each (cn, struct contrasts_node, ll, &cmd->contrast_list)
- {
- int contrast_idx = pivot_category_create_leaf (
- contrast->root, pivot_value_new_integer (c_num++));
-
- 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 struct ccase *gcc = categoricals_get_case_by_category (
- cats, indep_idx);
-
- if (!contrast_idx)
- pivot_category_create_leaf (
- indep_var->root, pivot_value_new_var_value (
- cmd->indep_var, case_data (gcc, cmd->indep_var)));
-
- pivot_table_put2 (table, indep_idx++, contrast_idx,
- pivot_value_new_integer (coeffn->coeff));
- }
- }
-
- 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);
- for (int i = 1; i <= n_contrasts; i++)
- pivot_category_create_leaf (contrasts->root, pivot_value_new_integer (i));
-
- pivot_dimension_create (table, PIVOT_AXIS_ROW, N_("Assumption"),
- N_("Assume equal variances"),
- N_("Does not assume equal variances"));
-
- struct pivot_dimension *variables = pivot_dimension_create (
- table, PIVOT_AXIS_ROW, N_("Dependent Variable"));
-
- 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);
- if (!categoricals_is_complete (cats))
- continue;
-
- int var_idx = pivot_category_create_leaf (
- variables->root, pivot_value_new_variable (cmd->vars[v]));
-
- struct contrasts_node *cn;
- int contrast_idx = 0;
- ll_for_each (cn, struct contrasts_node, ll, &cmd->contrast_list)
- {
-
- /* Note: The calculation of the degrees of freedom in the
- "variances not equal" case is painfull!!
- The following formula may help to understand it:
- \frac{\left (\sum_{i=1}^k{c_i^2\frac{s_i^2}{n_i}}\right)^2}
- {
- \sum_{i=1}^k\left (
- \frac{\left (c_i^2\frac{s_i^2}{n_i}\right)^2} {n_i-1}
- \right)
- }
- */
-
- double grand_n;
- moments1_calculate (ws->dd_total[v]->mom, &grand_n, NULL, NULL,
- NULL, NULL);
- double df = grand_n - pvw->n_groups;
-
- 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)
- {
- const struct descriptive_data *dd
- = categoricals_get_user_data_by_category (cats, ci);
- const double coef = coeffn->coeff;
-
- double n, mean, variance;
- moments1_calculate (dd->mom, &n, &mean, &variance, NULL, NULL);
-
- 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);
-
- ci++;
- }
- sec_vneq = sqrt (sec_vneq);
- df_numerator = pow2 (df_numerator);
-
- 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));
- }
-
- contrast_idx++;
- }
- }
-
- pivot_table_submit (table);
-}
-
-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)));
- }
-
- struct pivot_dimension *test = pivot_dimension_create (
- table, PIVOT_AXIS_ROW, N_("Test"));
-
- for (int p = 0; p < cmd->n_posthoc; ++p)
- {
- const struct posthoc *ph = &ph_tests[cmd->posthoc[p]];
-
- int test_idx = pivot_category_create_leaf (
- test->root, pivot_value_new_text (ph->label));
-
- 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);
-
- for (int j = 0; j < pvw->n_groups; ++j)
- {
- if (j == i)
- continue;
-
- 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]));
- }
- }
- }
-
- pivot_table_submit (table);
-}
projects / pspp / blobdiff