#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)
/* The weight variable */
const struct variable *wv;
+ const struct fmt_spec *wfmt;
/* The confidence level for multiple comparisons */
double alpha;
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;
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 pivot_table *table = pivot_table_create (N_("ANOVA"));
- struct tab_table *t = tab_create (n_cols, n_rows);
+ 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_headers (t, 2, 0, 1, 0);
+ pivot_dimension_create (table, PIVOT_AXIS_ROW, N_("Type"),
+ N_("Between Groups"), N_("Within Groups"),
+ N_("Total"));
- 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_("Variables"));
- 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);
-
- 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, _("Sig."));
-
-
- 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, RC_OTHER);
- tab_double (t, 2, i * 3 + 3, 0, pvw->sst, NULL, RC_OTHER);
- tab_double (t, 2, i * 3 + 2, 0, pvw->sse, NULL, RC_OTHER);
-
-
- /* Degrees of freedom */
- tab_double (t, 3, i * 3 + 1, 0, df1, NULL, RC_INTEGER);
- tab_double (t, 3, i * 3 + 2, 0, df2, NULL, RC_INTEGER);
- tab_double (t, 3, i * 3 + 3, 0, n - 1, NULL, RC_INTEGER);
+ double df1 = pvw->n_groups - 1;
+ double df2 = n - pvw->n_groups;
+ double msa = pvw->ssa / df1;
+ double F = msa / pvw->mse ;
- /* Mean Squares */
- tab_double (t, 4, i * 3 + 1, TAB_RIGHT, msa, NULL, RC_OTHER);
- tab_double (t, 4, i * 3 + 2, TAB_RIGHT, pvw->mse, NULL, RC_OTHER);
-
- {
- const double F = msa / pvw->mse ;
-
- /* The F value */
- tab_double (t, 5, i * 3 + 1, 0, F, NULL, RC_OTHER);
-
- /* The significance */
- tab_double (t, 6, i * 3 + 1, 0, gsl_cdf_fdist_Q (F, df1, df2), NULL, RC_PVALUE);
- }
+ 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_set_format (t, RC_WEIGHT, wfmt);
- 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"));
+ 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);
- 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);
-
- tab_text (t, 6, 1, TAB_CENTER | TAT_TITLE, _("Lower Bound"));
- tab_text (t, 7, 1, TAB_CENTER | TAT_TITLE, _("Upper Bound"));
-
- 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, NULL, RC_WEIGHT);
-
- tab_double (t, 3, row + count, 0, mean, NULL, RC_OTHER);
-
- tab_double (t, 4, row + count, 0, std_dev, NULL, RC_OTHER);
-
-
- tab_double (t, 5, row + count, 0, std_error, NULL, RC_OTHER);
-
- /* Now the confidence interval */
-
- T = gsl_cdf_tdist_Qinv (q, n - 1);
-
- tab_double (t, 6, row + count, 0,
- mean - T * std_error, NULL, RC_OTHER);
-
- tab_double (t, 7, row + count, 0,
- mean + T * std_error, NULL, RC_OTHER);
-
- /* Min and Max */
-
- tab_double (t, 8, row + count, 0, dd->minimum, fmt, RC_OTHER);
- tab_double (t, 9, row + count, 0, dd->maximum, fmt, RC_OTHER);
+ 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 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, NULL, RC_WEIGHT);
-
- tab_double (t, 3, row + count, 0, mean, NULL, RC_OTHER);
-
- tab_double (t, 4, row + count, 0, std_dev, NULL, RC_OTHER);
-
- tab_double (t, 5, row + count, 0, std_error, NULL, RC_OTHER);
-
- /* Now the confidence interval */
- T = gsl_cdf_tdist_Qinv (q, n - 1);
-
- tab_double (t, 6, row + count, 0,
- mean - T * std_error, NULL, RC_OTHER);
-
- tab_double (t, 7, row + count, 0,
- mean + T * std_error, NULL, RC_OTHER);
-
-
- /* Min and Max */
- tab_double (t, 8, row + count, 0, ws->dd_total[v]->minimum, fmt, RC_OTHER);
- tab_double (t, 9, row + count, 0, ws->dd_total[v]->maximum, fmt, RC_OTHER);
- }
-
- row += categoricals_n_total (cats) + 1;
+ {
+ 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, _("Sig."));
-
- 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, RC_OTHER);
- tab_double (t, 2, v + 1, TAB_RIGHT, df1, NULL, RC_INTEGER);
- tab_double (t, 3, v + 1, TAB_RIGHT, df2, NULL, RC_INTEGER);
+ 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, RC_PVALUE);
+ 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 tab_table *t;
-
- const struct covariance *cov = ws->vws[0].cov ;
-
- t = tab_create (n_cols, n_rows);
- tab_headers (t, 2, 0, 2, 0);
+ struct pivot_table *table = pivot_table_create (N_("Contrast Coefficients"));
- /* 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 *indep_var = pivot_dimension_create__ (
+ table, PIVOT_AXIS_COLUMN, pivot_value_new_variable (cmd->indep_var));
+ indep_var->root->show_label = true;
- tab_box (t,
- -1, -1,
- TAL_0, TAL_0,
- 2, 0,
- n_cols - 1, 0);
+ struct pivot_dimension *contrast = pivot_dimension_create (
+ table, PIVOT_AXIS_ROW, N_("Contrast"));
+ contrast->root->show_label = true;
- tab_box (t,
- -1, -1,
- TAL_0, TAL_0,
- 0, 0,
- 1, 1);
+ const struct covariance *cov = ws->vws[0].cov;
- 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 ;
+ int contrast_idx = pivot_category_create_leaf (
+ contrast->root, pivot_value_new_integer (c_num++));
- tab_text_format (t, 1, c_num + 2, TAB_CENTER, "%d", c_num + 1);
-
- 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",
- DBL_DIG + 1, 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);
if (!categoricals_is_complete (cats))
continue;
- struct ll *cli;
- int i = 0;
- int lines_per_variable = 2 * n_contrasts;
- 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, RC_OTHER);
-
- tab_double (t, 3, (v * lines_per_variable) + i + 1 +
- n_contrasts,
- TAB_RIGHT, contrast_value, NULL, RC_OTHER);
-
- 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, RC_OTHER);
+ double std_error_contrast = sqrt (pvw->mse * coef_msq);
+ double T = fabs (contrast_value / std_error_contrast);
+ double T_ne = contrast_value / sec_vneq;
+ double df_ne = df_numerator / df_denominator;
+ double p_ne = gsl_cdf_tdist_P (T_ne, df_ne);
+ double q_ne = gsl_cdf_tdist_Q (T_ne, df_ne);
- T = fabs (contrast_value / std_error_contrast);
-
- /* T Statistic */
-
- tab_double (t, 5, (v * lines_per_variable) + i + 1,
- TAB_RIGHT, T,
- NULL, RC_OTHER);
-
-
- /* Degrees of Freedom */
- tab_double (t, 6, (v * lines_per_variable) + i + 1,
- TAB_RIGHT, df, NULL, RC_INTEGER);
-
-
- /* Significance TWO TAILED !!*/
- tab_double (t, 7, (v * lines_per_variable) + i + 1,
- TAB_RIGHT, 2 * gsl_cdf_tdist_Q (T, df),
- NULL, RC_PVALUE);
-
- /* 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, RC_OTHER);
-
- T = contrast_value / sec_vneq;
- tab_double (t, 5,
- (v * lines_per_variable) + i + 1 + n_contrasts,
- TAB_RIGHT, T,
- NULL, RC_OTHER);
-
- df = df_numerator / df_denominator;
-
- tab_double (t, 6,
- (v * lines_per_variable) + i + 1 + n_contrasts,
- TAB_RIGHT, df,
- NULL, RC_OTHER);
-
- {
- double p = gsl_cdf_tdist_P (T, df);
- double q = gsl_cdf_tdist_Q (T, df);
+ 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 (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 * (T > 0 ? q_ne : p_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 * ((T > 0) ? q : p),
- NULL, RC_PVALUE);
- }
+ 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]))));
+ table->omit_empty = true;
+
+ 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 (%s)"), var_to_string (cmd->vars[v]));
-
- 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, NULL, RC_OTHER);
-
- 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, NULL, RC_OTHER);
-
- tab_double (t, 5, r + rx, 0, 2 * multiple_comparison_sig (std_err, pvw, dd_i, dd_j, ph), NULL, RC_PVALUE);
-
- 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, NULL, RC_OTHER);
-
- tab_double (t, 7, r + rx, 0,
- (mean_i - mean_j) + half_range, NULL, RC_OTHER);
-
- 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