/* PSPP - a program for statistical analysis.
- Copyright (C) 2011 Free Software Foundation, Inc.
+ Copyright (C) 2011, 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 "data/dictionary.h"
#include "data/format.h"
#include "data/variable.h"
-
#include "math/moments.h"
#include "math/levene.h"
+#include "output/pivot-table.h"
-#include <output/tab.h>
#include "gettext.h"
+#define N_(msgid) msgid
#define _(msgid) gettext (msgid)
{
int width = var_get_width (is->gvar);
int cmp = value_compare_3way (v, is->gval0, width);
- if ( is->cut )
+ if (is->cut)
return (cmp < 0);
if (cmp == 0)
struct ccase *c;
struct casereader *r;
- struct pair_stats *ps = xcalloc (tt->n_vars, sizeof *ps);
+ struct pair_stats *ps = XCALLOC (tt->n_vars, struct pair_stats);
int v;
is.cut = cut;
r = casereader_clone (reader);
- for ( ; (c = casereader_read (r) ); case_unref (c))
+ for (; (c = casereader_read (r)); case_unref (c))
{
double w = dict_get_case_weight (tt->dict, c, NULL);
const union value *gv = case_data (c, gvar);
-
+
int grp = which_group (gv, &is);
- if ( grp < 0)
+ if (grp < 0)
continue;
for (v = 0; v < tt->n_vars; ++v)
{
const union value *val = case_data (c, tt->vars[v]);
- if (var_is_value_missing (tt->vars[v], val, tt->exclude))
+ if (var_is_value_missing (tt->vars[v], val) & tt->exclude)
continue;
moments_pass_one (ps[v].mom[grp], val->f, w);
casereader_destroy (r);
r = casereader_clone (reader);
- for ( ; (c = casereader_read (r) ); case_unref (c))
+ for (; (c = casereader_read (r)); case_unref (c))
{
double w = dict_get_case_weight (tt->dict, c, NULL);
const union value *gv = case_data (c, gvar);
int grp = which_group (gv, &is);
- if ( grp < 0)
+ if (grp < 0)
continue;
for (v = 0; v < tt->n_vars; ++v)
{
const union value *val = case_data (c, tt->vars[v]);
- if (var_is_value_missing (tt->vars[v], val, tt->exclude))
+ if (var_is_value_missing (tt->vars[v], val) & tt->exclude)
continue;
moments_pass_two (ps[v].mom[grp], val->f, w);
casereader_destroy (r);
r = reader;
- for ( ; (c = casereader_read (r) ); case_unref (c))
+ for (; (c = casereader_read (r)); case_unref (c))
{
double w = dict_get_case_weight (tt->dict, c, NULL);
const union value *gv = case_data (c, gvar);
int grp = which_group (gv, &is);
- if ( grp < 0)
+ if (grp < 0)
continue;
for (v = 0; v < tt->n_vars; ++v)
{
const union value *val = case_data (c, tt->vars[v]);
- if (var_is_value_missing (tt->vars[v], val, tt->exclude))
+ if (var_is_value_missing (tt->vars[v], val) & tt->exclude)
continue;
levene_pass_three (ps[v].nl, val->f, w, gv);
for (v = 0; v < tt->n_vars; ++v)
ps[v].lev = levene_calculate (ps[v].nl);
-
+
indep_summary (tt, &is, ps);
indep_test (tt, ps);
static void
indep_summary (const struct tt *tt, struct indep_samples *is, const struct pair_stats *ps)
{
- const struct fmt_spec *wfmt = tt->wv ? var_get_print_format (tt->wv) : & F_8_0;
-
- int v;
- int cols = 6;
- const int heading_rows = 1;
- int rows = tt->n_vars * 2 + heading_rows;
-
- struct string vallab0 ;
- struct string vallab1 ;
- struct tab_table *t = tab_create (cols, rows);
-
- ds_init_empty (&vallab0);
- ds_init_empty (&vallab1);
-
- tab_headers (t, 0, 0, 1, 0);
- tab_box (t, TAL_2, TAL_2, TAL_0, TAL_1, 0, 0, cols - 1, rows - 1);
- tab_hline (t, TAL_2, 0, cols - 1, 1);
-
- tab_vline (t, TAL_GAP, 1, 0, rows - 1);
- tab_title (t, _("Group Statistics"));
- tab_text (t, 1, 0, TAB_CENTER | TAT_TITLE, var_to_string (is->gvar));
- tab_text (t, 2, 0, TAB_CENTER | TAT_TITLE, _("N"));
- tab_text (t, 3, 0, TAB_CENTER | TAT_TITLE, _("Mean"));
- tab_text (t, 4, 0, TAB_CENTER | TAT_TITLE, _("Std. Deviation"));
- tab_text (t, 5, 0, TAB_CENTER | TAT_TITLE, _("S.E. Mean"));
-
+ struct pivot_table *table = pivot_table_create (N_("Group Statistics"));
+ pivot_table_set_weight_var (table, tt->wv);
+
+ pivot_dimension_create (table, PIVOT_AXIS_COLUMN, N_("Statistics"),
+ N_("N"), PIVOT_RC_COUNT,
+ N_("Mean"), PIVOT_RC_OTHER,
+ N_("Std. Deviation"), PIVOT_RC_OTHER,
+ N_("S.E. Mean"), PIVOT_RC_OTHER);
+
+ struct pivot_dimension *group = pivot_dimension_create (
+ table, PIVOT_AXIS_ROW, N_("Group"));
+ group->root->show_label = true;
if (is->cut)
{
+ struct string vallab0 = DS_EMPTY_INITIALIZER;
ds_put_cstr (&vallab0, "≥");
- ds_put_cstr (&vallab1, "<");
-
var_append_value_name (is->gvar, is->gval0, &vallab0);
+ pivot_category_create_leaf (group->root,
+ pivot_value_new_user_text_nocopy (
+ ds_steal_cstr (&vallab0)));
+
+ struct string vallab1 = DS_EMPTY_INITIALIZER;
+ ds_put_cstr (&vallab1, "<");
var_append_value_name (is->gvar, is->gval0, &vallab1);
+ pivot_category_create_leaf (group->root,
+ pivot_value_new_user_text_nocopy (
+ ds_steal_cstr (&vallab1)));
}
else
{
- var_append_value_name (is->gvar, is->gval0, &vallab0);
- var_append_value_name (is->gvar, is->gval1, &vallab1);
+ pivot_category_create_leaf (
+ group->root, pivot_value_new_var_value (is->gvar, is->gval0));
+ pivot_category_create_leaf (
+ group->root, pivot_value_new_var_value (is->gvar, is->gval1));
}
- tab_vline (t, TAL_1, 1, heading_rows, rows - 1);
+ struct pivot_dimension *dep_vars = pivot_dimension_create (
+ table, PIVOT_AXIS_ROW, N_("Dependent Variables"));
- for (v = 0; v < tt->n_vars; ++v)
+ for (size_t v = 0; v < tt->n_vars; ++v)
{
- int i;
const struct variable *var = tt->vars[v];
- tab_text (t, 0, v * 2 + heading_rows, TAB_LEFT,
- var_to_string (var));
-
- tab_text (t, 1, v * 2 + heading_rows, TAB_LEFT,
- ds_cstr (&vallab0));
+ int dep_var_idx = pivot_category_create_leaf (
+ dep_vars->root, pivot_value_new_variable (var));
- tab_text (t, 1, v * 2 + 1 + heading_rows, TAB_LEFT,
- ds_cstr (&vallab1));
-
- for (i = 0 ; i < 2; ++i)
+ for (int i = 0 ; i < 2; ++i)
{
double cc, mean, sigma;
moments_calculate (ps[v].mom[i], &cc, &mean, &sigma, NULL, NULL);
-
- tab_double (t, 2, v * 2 + i + heading_rows, TAB_RIGHT, cc, wfmt);
- tab_double (t, 3, v * 2 + i + heading_rows, TAB_RIGHT, mean, NULL);
- tab_double (t, 4, v * 2 + i + heading_rows, TAB_RIGHT, sqrt (sigma), NULL);
- tab_double (t, 5, v * 2 + i + heading_rows, TAB_RIGHT, sqrt (sigma / cc), NULL);
+
+ double entries[] = { cc, mean, sqrt (sigma), sqrt (sigma / cc) };
+ for (size_t j = 0; j < sizeof entries / sizeof *entries; j++)
+ pivot_table_put3 (table, j, i, dep_var_idx,
+ pivot_value_new_number (entries[j]));
}
}
- tab_submit (t);
-
- ds_destroy (&vallab0);
- ds_destroy (&vallab1);
+ pivot_table_submit (table);
}
static void
indep_test (const struct tt *tt, const struct pair_stats *ps)
{
- int v;
- const int heading_rows = 3;
- const int rows= tt->n_vars * 2 + heading_rows;
-
- const size_t cols = 11;
-
- struct tab_table *t = tab_create (cols, rows);
- tab_headers (t, 0, 0, 3, 0);
- tab_box (t, TAL_2, TAL_2, TAL_0, TAL_0, 0, 0, cols - 1, rows - 1);
- tab_hline (t, TAL_2, 0, cols - 1, 3);
-
- tab_title (t, _("Independent Samples Test"));
-
- tab_hline (t, TAL_1, 2, cols - 1, 1);
- tab_vline (t, TAL_2, 2, 0, rows - 1);
- tab_vline (t, TAL_1, 4, 0, rows - 1);
- tab_box (t, -1, -1, -1, TAL_1, 2, 1, cols - 2, rows - 1);
- tab_hline (t, TAL_1, cols - 2, cols - 1, 2);
- tab_box (t, -1, -1, -1, TAL_1, cols - 2, 2, cols - 1, rows - 1);
- tab_joint_text (t, 2, 0, 3, 0, TAB_CENTER, _("Levene's Test for Equality of Variances"));
- tab_joint_text (t, 4, 0, cols - 1, 0, TAB_CENTER, _("t-test for Equality of Means"));
-
- tab_text (t, 2, 2, TAB_CENTER | TAT_TITLE, _("F"));
- tab_text (t, 3, 2, TAB_CENTER | TAT_TITLE, _("Sig."));
- tab_text (t, 4, 2, TAB_CENTER | TAT_TITLE, _("t"));
- tab_text (t, 5, 2, TAB_CENTER | TAT_TITLE, _("df"));
- tab_text (t, 6, 2, TAB_CENTER | TAT_TITLE, _("Sig. (2-tailed)"));
- tab_text (t, 7, 2, TAB_CENTER | TAT_TITLE, _("Mean Difference"));
- tab_text (t, 8, 2, TAB_CENTER | TAT_TITLE, _("Std. Error Difference"));
- tab_text (t, 9, 2, TAB_CENTER | TAT_TITLE, _("Lower"));
- tab_text (t, 10, 2, TAB_CENTER | TAT_TITLE, _("Upper"));
-
- tab_joint_text_format (t, 9, 1, 10, 1, TAB_CENTER,
- _("%g%% Confidence Interval of the Difference"),
- tt->confidence * 100.0);
-
- tab_vline (t, TAL_1, 1, heading_rows, rows - 1);
-
- for (v = 0; v < tt->n_vars; ++v)
+ struct pivot_table *table = pivot_table_create (
+ N_("Independent Samples Test"));
+
+ struct pivot_dimension *statistics = pivot_dimension_create (
+ table, PIVOT_AXIS_COLUMN, N_("Statistics"));
+ pivot_category_create_group (
+ statistics->root, N_("Levene's Test for Equality of Variances"),
+ N_("F"), PIVOT_RC_OTHER,
+ N_("Sig."), PIVOT_RC_SIGNIFICANCE);
+ struct pivot_category *group = pivot_category_create_group (
+ statistics->root, N_("T-Test for Equality of Means"),
+ N_("t"), PIVOT_RC_OTHER,
+ N_("df"), PIVOT_RC_OTHER,
+ N_("Sig. (2-tailed)"), PIVOT_RC_SIGNIFICANCE,
+ N_("Mean Difference"), PIVOT_RC_OTHER,
+ N_("Std. Error Difference"), PIVOT_RC_OTHER);
+ pivot_category_create_group (
+ /* xgettext:no-c-format */
+ group, N_("95% Confidence Interval of the Difference"),
+ N_("Lower"), PIVOT_RC_OTHER,
+ N_("Upper"), PIVOT_RC_OTHER);
+
+ pivot_dimension_create (table, PIVOT_AXIS_ROW, N_("Assumptions"),
+ N_("Equal variances assumed"),
+ N_("Equal variances not assumed"));
+
+ struct pivot_dimension *dep_vars = pivot_dimension_create (
+ table, PIVOT_AXIS_ROW, N_("Dependent Variables"));
+
+ for (size_t v = 0; v < tt->n_vars; ++v)
{
- double df, pooled_variance, mean_diff, tval;
- double se2, std_err_diff;
- double p, q;
+ int dep_var_idx = pivot_category_create_leaf (
+ dep_vars->root, pivot_value_new_variable (tt->vars[v]));
+
double cc0, mean0, sigma0;
double cc1, mean1, sigma1;
moments_calculate (ps[v].mom[0], &cc0, &mean0, &sigma0, NULL, NULL);
moments_calculate (ps[v].mom[1], &cc1, &mean1, &sigma1, NULL, NULL);
- tab_text (t, 0, v * 2 + heading_rows, TAB_LEFT, var_to_string (tt->vars[v]));
- tab_text (t, 1, v * 2 + heading_rows, TAB_LEFT, _("Equal variances assumed"));
-
- df = cc0 + cc1 - 2.0;
- tab_double (t, 5, v * 2 + heading_rows, TAB_RIGHT, df, NULL);
-
- pooled_variance = ((cc0 - 1)* sigma0 + (cc1 - 1) * sigma1) / df ;
-
- tval = (mean0 - mean1) / sqrt (pooled_variance);
- tval /= sqrt ((cc0 + cc1) / (cc0 * cc1));
-
- tab_double (t, 4, v * 2 + heading_rows, TAB_RIGHT, tval, NULL);
-
- p = gsl_cdf_tdist_P (tval, df);
- q = gsl_cdf_tdist_Q (tval, df);
-
- mean_diff = mean0 - mean1;
+ double mean_diff = mean0 - mean1;
- tab_double (t, 6, v * 2 + heading_rows, TAB_RIGHT, 2.0 * (tval > 0 ? q : p), NULL);
- tab_double (t, 7, v * 2 + heading_rows, TAB_RIGHT, mean_diff, NULL);
- std_err_diff = sqrt (pooled_variance * (1.0/cc0 + 1.0/cc1));
- tab_double (t, 8, v * 2 + heading_rows, TAB_RIGHT, std_err_diff, NULL);
-
-
- /* Now work out the confidence interval */
- q = (1 - tt->confidence)/2.0; /* 2-tailed test */
-
- tval = gsl_cdf_tdist_Qinv (q, df);
- tab_double (t, 9, v * 2 + heading_rows, TAB_RIGHT, mean_diff - tval * std_err_diff, NULL);
- tab_double (t, 10, v * 2 + heading_rows, TAB_RIGHT, mean_diff + tval * std_err_diff, NULL);
+ /* Equal variances assumed. */
+ double e_df = cc0 + cc1 - 2.0;
+ double e_pooled_variance = ((cc0 - 1)* sigma0 + (cc1 - 1) * sigma1) / e_df;
+ double e_tval = ((mean0 - mean1) / sqrt (e_pooled_variance)
+ / sqrt ((cc0 + cc1) / (cc0 * cc1)));
+ double e_p = gsl_cdf_tdist_P (e_tval, e_df);
+ double e_q = gsl_cdf_tdist_Q (e_tval, e_df);
+ double e_sig = 2.0 * (e_tval > 0 ? e_q : e_p);
+ double e_std_err_diff = sqrt (e_pooled_variance * (1.0/cc0 + 1.0/cc1));
+ double e_tval_qinv = gsl_cdf_tdist_Qinv ((1 - tt->confidence) / 2.0, e_df);
/* Equal variances not assumed */
- tab_text (t, 1, v * 2 + heading_rows + 1, TAB_LEFT, _("Equal variances not assumed"));
- std_err_diff = sqrt ((sigma0 / cc0) + (sigma1 / cc1));
-
- se2 = sigma0 / cc0 + sigma1 / cc1;
- tval = mean_diff / sqrt (se2);
- tab_double (t, 4, v * 2 + heading_rows + 1, TAB_RIGHT, tval, NULL);
-
- {
- double p, q;
- const double s0 = sigma0 / (cc0);
- const double s1 = sigma1 / (cc1);
- double df = pow2 (s0 + s1) ;
- df /= pow2 (s0) / (cc0 - 1) + pow2 (s1) / (cc1 - 1);
-
- tab_double (t, 5, v * 2 + heading_rows + 1, TAB_RIGHT, df, NULL);
-
- p = gsl_cdf_tdist_P (tval, df);
- q = gsl_cdf_tdist_Q (tval, df);
-
- tab_double (t, 6, v * 2 + heading_rows + 1, TAB_RIGHT, 2.0 * (tval > 0 ? q : p), NULL);
-
- /* Now work out the confidence interval */
- q = (1 - tt->confidence) / 2.0; /* 2-tailed test */
-
- tval = gsl_cdf_tdist_Qinv (q, df);
- }
-
- tab_double (t, 7, v * 2 + heading_rows + 1, TAB_RIGHT, mean_diff, NULL);
- tab_double (t, 8, v * 2 + heading_rows + 1, TAB_RIGHT, std_err_diff, NULL);
- tab_double (t, 9, v * 2 + heading_rows + 1, TAB_RIGHT, mean_diff - tval * std_err_diff, NULL);
- tab_double (t, 10, v * 2 + heading_rows + 1, TAB_RIGHT, mean_diff + tval * std_err_diff, NULL);
-
- tab_double (t, 2, v * 2 + heading_rows, TAB_CENTER, ps[v].lev, NULL);
-
-
- {
- /* Now work out the significance of the Levene test */
- double df1 = 1;
- double df2 = cc0 + cc1 - 2;
- double q = gsl_cdf_fdist_Q (ps[v].lev, df1, df2);
- tab_double (t, 3, v * 2 + heading_rows, TAB_CENTER, q, NULL);
- }
+ const double s0 = sigma0 / cc0;
+ const double s1 = sigma1 / cc1;
+ double d_df = (pow2 (s0 + s1) / (pow2 (s0) / (cc0 - 1)
+ + pow2 (s1) / (cc1 - 1)));
+ double d_tval = mean_diff / sqrt (sigma0 / cc0 + sigma1 / cc1);
+ double d_p = gsl_cdf_tdist_P (d_tval, d_df);
+ double d_q = gsl_cdf_tdist_Q (d_tval, d_df);
+ double d_sig = 2.0 * (d_tval > 0 ? d_q : d_p);
+ double d_std_err_diff = sqrt ((sigma0 / cc0) + (sigma1 / cc1));
+ double d_tval_qinv = gsl_cdf_tdist_Qinv ((1 - tt->confidence) / 2.0, d_df);
+
+ struct entry
+ {
+ int assumption_idx;
+ int stat_idx;
+ double x;
+ }
+ entries[] =
+ {
+ { 0, 0, ps[v].lev },
+ { 0, 1, gsl_cdf_fdist_Q (ps[v].lev, 1, cc0 + cc1 - 2) },
+
+ { 0, 2, e_tval },
+ { 0, 3, e_df },
+ { 0, 4, e_sig },
+ { 0, 5, mean_diff },
+ { 0, 6, e_std_err_diff },
+ { 0, 7, mean_diff - e_tval_qinv * e_std_err_diff },
+ { 0, 8, mean_diff + e_tval_qinv * e_std_err_diff },
+
+ { 1, 2, d_tval },
+ { 1, 3, d_df },
+ { 1, 4, d_sig },
+ { 1, 5, mean_diff },
+ { 1, 6, d_std_err_diff },
+ { 1, 7, mean_diff - d_tval_qinv * d_std_err_diff },
+ { 1, 8, mean_diff + d_tval_qinv * d_std_err_diff },
+ };
+
+ for (size_t i = 0; i < sizeof entries / sizeof *entries; i++)
+ {
+ const struct entry *e = &entries[i];
+ pivot_table_put3 (table, e->stat_idx, e->assumption_idx,
+ dep_var_idx, pivot_value_new_number (e->x));
+ }
}
- tab_submit (t);
+ pivot_table_submit (table);
}