/* PSPP - a program for statistical analysis.
- Copyright (C) 1997-9, 2000, 2007, 2009, 2010, 2011 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
#include <config.h>
+#include <float.h>
#include <gsl/gsl_cdf.h>
#include <gsl/gsl_matrix.h>
#include <math.h>
#include "math/covariance.h"
#include "math/levene.h"
#include "math/moments.h"
-#include "output/tab.h"
+#include "output/pivot-table.h"
#include "gettext.h"
#define _(msgid) gettext (msgid)
/* Workspace variable for each dependent variable */
struct per_var_ws
{
+ struct interaction *iact;
struct categoricals *cat;
struct covariance *cov;
struct levene *nl;
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;
};
/* The weight variable */
const struct variable *wv;
+ const struct fmt_spec *wfmt;
/* The confidence level for multiple comparisons */
double alpha;
double n_j, var_j;
double nom,denom;
- moments1_calculate (mom_i, &n_i, NULL, &var_i, 0, 0);
+ 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);
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 ) ;
+ 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);
}
double n_j, mean_j, var_j;
double m;
- moments1_calculate (mom_i, &n_i, &mean_i, &var_i, 0, 0);
+ 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
+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,
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
+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 = 1.0 - ptukey (ts, 1.0, df1 + 1, df2, 1, 0);
+ 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;
}
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_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;
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_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;
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_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;
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_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;
-static const struct posthoc ph_tests [] =
+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},
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;
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"))
{
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)
{
break;
}
}
- if ( method == false)
+ if (method == false)
{
if (lex_match_id (lexer, "ALPHA"))
{
- if ( !lex_force_match (lexer, T_LPAREN))
+ if (!lex_force_match (lexer, T_LPAREN))
+ goto error;
+ if (! lex_force_num (lexer))
goto error;
- lex_force_num (lexer);
oneway.alpha = lex_number (lexer);
lex_get (lexer);
- if ( !lex_force_match (lexer, T_RPAREN))
+ if (!lex_force_match (lexer, T_RPAREN))
goto error;
}
else
}
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);
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);
}
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"))
ok = proc_commit (ds) && ok;
}
+ oneway_cleanup (&oneway);
free (oneway.vars);
return CMD_SUCCESS;
error:
+ oneway_cleanup (&oneway);
free (oneway.vars);
return CMD_FAILURE;
}
}
static void *
-makeit (void *aux1, void *aux2 UNUSED)
+makeit (const void *aux1, void *aux2 UNUSED)
{
const struct variable *var = aux1;
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)
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)
{
- struct interaction *inter = interaction_create (cmd->indep_var);
- ws.vws[v].cat = categoricals_create (&inter, 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);
}
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;
}
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);
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;
}
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);
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;
}
for (v = 0; v < cmd->n_vars; ++v)
{
+ const gsl_matrix *ucm;
+ gsl_matrix *cm;
struct per_var_ws *pvw = &ws.vws[v];
const struct categoricals *cats = covariance_get_categoricals (pvw->cov);
- categoricals_done (cats);
+ const bool ok = categoricals_sane (cats);
+
+ 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;
+ }
+
+ ucm = covariance_calculate_unnormalized (pvw->cov);
- gsl_matrix *cm = covariance_calculate_unnormalized (pvw->cov);
+ 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);
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);
-
- gsl_matrix_free (cm);
}
for (v = 0; v < cmd->n_vars; ++v)
{
const struct categoricals *cats = covariance_get_categoricals (ws.vws[v].cov);
+ 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);
}
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);
}
if (ll_count (cl) != ws->actual_number_of_groups)
{
msg (SW,
- _("In contrast list %zu, the number of coefficients (%d) does not equal the number of groups (%d). This contrast list will be ignored."),
+ _("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);
}
show_contrast_tests (cmd, ws);
}
- if ( cmd->posthoc )
+ if (cmd->posthoc)
{
int v;
for (v = 0 ; v < cmd->n_vars; ++v)
- show_comparisons (cmd, ws, v);
+ {
+ const struct categoricals *cats = covariance_get_categoricals (ws->vws[v].cov);
+
+ if (categoricals_is_complete (cats))
+ show_comparisons (cmd, ws, v);
+ }
}
}
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);
-
- 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_("ANOVA"));
- 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_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_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"));
+ 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 (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);
-
+ 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 struct ccase *gcc = categoricals_get_case_by_category (cats, count);
- const struct descriptive_data *dd = categoricals_get_user_data_by_category (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, case_data (gcc, cmd->indep_var), &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_n_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"));
+ 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_hline (t, TAL_2, 0, n_cols - 1, 1);
- tab_vline (t, TAL_2, 1, 0, n_rows - 1);
+ struct pivot_dimension *variables = pivot_dimension_create (
+ table, PIVOT_AXIS_ROW, N_("Variables"));
- 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"));
-
- 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 = levene_calculate (pvw->nl);
-
- 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);
}
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 struct ccase *gcc = categoricals_get_case_by_category (cats, count);
- struct coeff_node *coeffn = ll_data (coeffi, struct coeff_node, ll);
- struct string vstr;
-
- ds_init_empty (&vstr);
-
- var_append_value_name (cmd->indep_var, case_data (gcc, cmd->indep_var), &vstr);
+ const struct ccase *gcc = categoricals_get_case_by_category (
+ cats, indep_idx);
- tab_text (t, count + 2, 1, TAB_CENTER | TAT_TITLE, ds_cstr (&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)));
- ds_destroy (&vstr);
-
- 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;
+ for (int i = 1; i <= n_contrasts; i++)
+ pivot_category_create_leaf (contrasts->root, pivot_value_new_integer (i));
- t = tab_create (n_cols, n_rows);
- tab_headers (t, 3, 0, 1, 0);
+ pivot_dimension_create (table, PIVOT_AXIS_ROW, N_("Assumption"),
+ N_("Assume equal variances"),
+ N_("Does not assume equal variances"));
- /* 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_dimension *variables = pivot_dimension_create (
+ table, PIVOT_AXIS_ROW, N_("Dependent Variable"));
- tab_box (t,
- -1, -1,
- TAL_0, TAL_0,
- 0, 0,
- 2, 0);
-
- 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!!
}
*/
- 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"));
-
- 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);
-
+ const struct descriptive_data *dd
+ = categoricals_get_user_data_by_category (cats, ci);
+ const double coef = coeffn->coeff;
- tab_text_format (t, 2,
- (v * lines_per_variable) + i + 1 + n_contrasts,
- TAB_CENTER | TAT_TITLE, "%d", i + 1);
-
- 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_category (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);
+ 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;
- 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);
-
-
- /* Degrees of Freedom */
- tab_fixed (t, 6, (v * lines_per_variable) + i + 1,
- TAB_RIGHT, df,
- 8, 0);
-
-
- /* Significance TWO TAILED !!*/
- tab_double (t, 7, (v * lines_per_variable) + i + 1,
- TAB_RIGHT, 2 * gsl_cdf_tdist_Q (T, df),
- NULL);
-
- /* Now for the Variances NOT Equal case */
-
- /* Std. Error */
- tab_double (t, 4,
- (v * lines_per_variable) + i + 1 + n_contrasts,
- TAB_RIGHT, sec_vneq,
- NULL);
-
- T = contrast_value / sec_vneq;
- tab_double (t, 5,
- (v * lines_per_variable) + i + 1 + n_contrasts,
- TAB_RIGHT, T,
- NULL);
-
- df = df_numerator / df_denominator;
-
- tab_double (t, 6,
- (v * lines_per_variable) + i + 1 + n_contrasts,
- TAB_RIGHT, df,
- NULL);
+ 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));
+ }
- /* The Significance */
- tab_double (t, 7, (v * lines_per_variable) + i + 1 + n_contrasts,
- TAB_RIGHT, 2 * gsl_cdf_tdist_Q (T,df),
- NULL);
+ contrast_idx++;
}
-
- if ( v > 0 )
- tab_hline (t, TAL_1, 0, n_cols - 1, (v * lines_per_variable) + 1);
}
- tab_submit (t);
+ pivot_table_submit (table);
}
-
-
static void
show_comparisons (const struct oneway_spec *cmd, const struct oneway_workspace *ws, int v)
{
- const int n_cols = 8;
- const int heading_rows = 2;
- const int heading_cols = 3;
-
- int p;
- int r = heading_rows ;
+ 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;
- const int n_rows = heading_rows + cmd->n_posthoc * pvw->n_groups * (pvw->n_groups - 1);
-
- struct tab_table *t = tab_create (n_cols, n_rows);
-
- tab_headers (t, heading_cols, 0, heading_rows, 0);
-
- /* Put a frame around the entire box, and vertical lines inside */
- tab_box (t,
- TAL_2, TAL_2,
- -1, -1,
- 0, 0,
- n_cols - 1, n_rows - 1);
-
- tab_box (t,
- -1, -1,
- -1, TAL_1,
- heading_cols, 0,
- n_cols - 1, n_rows - 1);
-
- tab_vline (t, TAL_2, heading_cols, 0, n_rows - 1);
-
- tab_title (t, _("Multiple Comparisons"));
-
- tab_text_format (t, 1, 1, TAB_LEFT | TAT_TITLE, _("(I) %s"), var_to_string (cmd->indep_var));
- tab_text_format (t, 2, 1, TAB_LEFT | TAT_TITLE, _("(J) %s"), var_to_string (cmd->indep_var));
- tab_text (t, 3, 0, TAB_CENTER | TAT_TITLE, _("Mean Difference"));
- tab_text (t, 3, 1, TAB_CENTER | TAT_TITLE, _("(I - J)"));
- tab_text (t, 4, 1, TAB_CENTER | TAT_TITLE, _("Std. Error"));
- tab_text (t, 5, 1, TAB_CENTER | TAT_TITLE, _("Sig."));
-
- tab_joint_text_format (t, 6, 0, 7, 0, TAB_CENTER | TAT_TITLE,
- _("%g%% Confidence Interval"),
- (1 - cmd->alpha) * 100.0);
-
- tab_text (t, 6, 1, TAB_CENTER | TAT_TITLE, _("Lower Bound"));
- tab_text (t, 7, 1, TAB_CENTER | TAT_TITLE, _("Upper Bound"));
+ 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 (p = 0; p < cmd->n_posthoc; ++p)
+ for (int p = 0; p < cmd->n_posthoc; ++p)
{
- int i;
const struct posthoc *ph = &ph_tests[cmd->posthoc[p]];
- tab_hline (t, TAL_2, 0, n_cols - 1, r);
-
- tab_text (t, 0, r, TAB_LEFT | TAT_TITLE, gettext (ph->label));
+ int test_idx = pivot_category_create_leaf (
+ test->root, pivot_value_new_text (ph->label));
- for (i = 0; i < pvw->n_groups ; ++i)
+ 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;
- int rx = 0;
- struct string vstr;
- int j;
- struct descriptive_data *dd_i = categoricals_get_user_data_by_category (cat, i);
- const struct ccase *gcc = categoricals_get_case_by_category (cat, i);
-
-
- ds_init_empty (&vstr);
- var_append_value_name (cmd->indep_var, case_data (gcc, cmd->indep_var), &vstr);
-
- if ( i != 0)
- tab_hline (t, TAL_1, 1, n_cols - 1, r);
- tab_text (t, 1, r, TAB_LEFT | TAT_TITLE, ds_cstr (&vstr));
-
moments1_calculate (dd_i->mom, &weight_i, &mean_i, &var_i, 0, 0);
- for (j = 0 ; j < pvw->n_groups; ++j)
+ for (int j = 0 ; j < pvw->n_groups; ++j)
{
- double std_err;
- double weight_j, mean_j, var_j;
- double half_range;
- const struct ccase *cc;
- struct descriptive_data *dd_j = categoricals_get_user_data_by_category (cat, j);
if (j == i)
continue;
- ds_clear (&vstr);
- cc = categoricals_get_case_by_category (cat, j);
- var_append_value_name (cmd->indep_var, case_data (cc, cmd->indep_var), &vstr);
- tab_text (t, 2, r + rx, TAB_LEFT | TAT_TITLE, ds_cstr (&vstr));
-
+ 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);
- tab_double (t, 3, r + rx, 0, mean_i - mean_j, 0);
-
- std_err = pvw->mse;
+ double std_err = pvw->mse;
std_err *= weight_i + weight_j;
std_err /= weight_i * weight_j;
std_err = sqrt (std_err);
- tab_double (t, 4, r + rx, 0, std_err, 0);
-
- tab_double (t, 5, r + rx, 0, 2 * multiple_comparison_sig (std_err, pvw, dd_i, dd_j, ph), 0);
-
- half_range = mc_half_range (cmd, pvw, std_err, dd_i, dd_j, ph);
-
- tab_double (t, 6, r + rx, 0,
- (mean_i - mean_j) - half_range, 0 );
-
- tab_double (t, 7, r + rx, 0,
- (mean_i - mean_j) + half_range, 0 );
-
- rx++;
+ 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]));
}
- ds_destroy (&vstr);
- r += pvw->n_groups - 1;
}
}
- tab_submit (t);
+ pivot_table_submit (table);
}
projects / pspp / blobdiff