--- /dev/null
+/* PSPP - a program for statistical analysis.
+ Copyright (C) 2009, 2010, 2011, 2013, 2015, 2016 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 <math.h>
+
+#include "data/casegrouper.h"
+#include "data/casereader.h"
+#include "data/dataset.h"
+#include "data/dictionary.h"
+#include "data/format.h"
+#include "data/missing-values.h"
+#include "language/command.h"
+#include "language/lexer/lexer.h"
+#include "language/lexer/variable-parser.h"
+#include "libpspp/message.h"
+#include "libpspp/misc.h"
+#include "libpspp/str.h"
+#include "math/moments.h"
+#include "output/pivot-table.h"
+#include "output/output-item.h"
+
+#include "gettext.h"
+#define _(msgid) gettext (msgid)
+#define N_(msgid) msgid
+
+struct cronbach
+ {
+ const struct variable **items;
+ size_t n_items;
+ double alpha;
+ double sum_of_variances;
+ double variance_of_sums;
+ int totals_idx; /* Casereader index into the totals */
+
+ struct moments1 **m; /* Moments of the items */
+ struct moments1 *total; /* Moments of the totals */
+ };
+
+#if 0
+static void
+dump_cronbach (const struct cronbach *s)
+{
+ int i;
+ printf ("N items %d\n", s->n_items);
+ for (i = 0; i < s->n_items; ++i)
+ {
+ printf ("%s\n", var_get_name (s->items[i]));
+ }
+
+ printf ("Totals idx %d\n", s->totals_idx);
+
+ printf ("scale variance %g\n", s->variance_of_sums);
+ printf ("alpha %g\n", s->alpha);
+ putchar ('\n');
+}
+#endif
+
+enum model
+ {
+ MODEL_ALPHA,
+ MODEL_SPLIT
+ };
+
+
+struct reliability
+{
+ const struct variable **vars;
+ size_t n_vars;
+ enum mv_class exclude;
+
+ struct cronbach *sc;
+ int n_sc;
+
+ int total_start;
+
+ char *scale_name;
+
+ enum model model;
+ int split_point;
+
+ bool summary_total;
+
+ const struct variable *wv;
+};
+
+
+static bool run_reliability (struct dataset *ds, const struct reliability *reliability);
+
+static void
+reliability_destroy (struct reliability *rel)
+{
+ int j;
+ free (rel->scale_name);
+ if (rel->sc)
+ for (j = 0; j < rel->n_sc; ++j)
+ {
+ int x;
+ free (rel->sc[j].items);
+ moments1_destroy (rel->sc[j].total);
+ if (rel->sc[j].m)
+ for (x = 0; x < rel->sc[j].n_items; ++x)
+ free (rel->sc[j].m[x]);
+ free (rel->sc[j].m);
+ }
+
+ free (rel->sc);
+ free (rel->vars);
+}
+
+int
+cmd_reliability (struct lexer *lexer, struct dataset *ds)
+{
+ const struct dictionary *dict = dataset_dict (ds);
+
+ struct reliability r = {
+ .model = MODEL_ALPHA,
+ .exclude = MV_ANY,
+ .wv = dict_get_weight (dict),
+ .scale_name = xstrdup ("ANY"),
+ };
+
+ lex_match (lexer, T_SLASH);
+
+ if (!lex_force_match_id (lexer, "VARIABLES"))
+ goto error;
+
+ lex_match (lexer, T_EQUALS);
+
+ int vars_start = lex_ofs (lexer);
+ if (!parse_variables_const (lexer, dict, &r.vars, &r.n_vars,
+ PV_NO_DUPLICATE | PV_NUMERIC))
+ goto error;
+ int vars_end = lex_ofs (lexer) - 1;
+
+ if (r.n_vars < 2)
+ lex_ofs_msg (lexer, SW, vars_start, vars_end,
+ _("Reliability on a single variable is not useful."));
+
+ /* Create a default scale. */
+ r.n_sc = 1;
+ r.sc = xcalloc (r.n_sc, sizeof (struct cronbach));
+
+ struct cronbach *c = &r.sc[0];
+ c->n_items = r.n_vars;
+ c->items = xcalloc (c->n_items, sizeof (struct variable*));
+ for (size_t i = 0; i < c->n_items; ++i)
+ c->items[i] = r.vars[i];
+
+ int split_ofs = 0;
+ while (lex_token (lexer) != T_ENDCMD)
+ {
+ lex_match (lexer, T_SLASH);
+
+ if (lex_match_id (lexer, "SCALE"))
+ {
+ struct const_var_set *vs;
+ if (!lex_force_match (lexer, T_LPAREN))
+ goto error;
+
+ if (!lex_force_string (lexer))
+ goto error;
+ free (r.scale_name);
+ r.scale_name = xstrdup (lex_tokcstr (lexer));
+ lex_get (lexer);
+
+ if (!lex_force_match (lexer, T_RPAREN))
+ goto error;
+
+ lex_match (lexer, T_EQUALS);
+
+ vs = const_var_set_create_from_array (r.vars, r.n_vars);
+
+ free (r.sc->items);
+ if (!parse_const_var_set_vars (lexer, vs, &r.sc->items, &r.sc->n_items, 0))
+ {
+ const_var_set_destroy (vs);
+ goto error;
+ }
+
+ const_var_set_destroy (vs);
+ }
+ else if (lex_match_id (lexer, "MODEL"))
+ {
+ lex_match (lexer, T_EQUALS);
+ if (lex_match_id (lexer, "ALPHA"))
+ r.model = MODEL_ALPHA;
+ else if (lex_match_id (lexer, "SPLIT"))
+ {
+ r.model = MODEL_SPLIT;
+ r.split_point = -1;
+
+ if (lex_match (lexer, T_LPAREN))
+ {
+ if (!lex_force_num (lexer))
+ goto error;
+ split_ofs = lex_ofs (lexer);
+ r.split_point = lex_number (lexer);
+ lex_get (lexer);
+ if (!lex_force_match (lexer, T_RPAREN))
+ goto error;
+ }
+ }
+ else
+ {
+ lex_error_expecting (lexer, "ALPHA", "SPLIT");
+ goto error;
+ }
+ }
+ else if (lex_match_id (lexer, "SUMMARY"))
+ {
+ lex_match (lexer, T_EQUALS);
+ if (lex_match_id (lexer, "TOTAL") || lex_match (lexer, T_ALL))
+ r.summary_total = true;
+ else
+ {
+ lex_error_expecting (lexer, "TOTAL", "ALL");
+ goto error;
+ }
+ }
+ 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"))
+ r.exclude = MV_SYSTEM;
+ else if (lex_match_id (lexer, "EXCLUDE"))
+ r.exclude = MV_ANY;
+ else
+ {
+ lex_error_expecting (lexer, "INCLUDE", "EXCLUDE");
+ goto error;
+ }
+ }
+ }
+ else if (lex_match_id (lexer, "STATISTICS"))
+ {
+ int statistics_start = lex_ofs (lexer) - 1;
+ lex_match (lexer, T_EQUALS);
+ while (lex_match (lexer, T_ID))
+ continue;
+ int statistics_end = lex_ofs (lexer) - 1;
+
+ lex_ofs_msg (lexer, SW, statistics_start, statistics_end,
+ _("The STATISTICS subcommand is not yet implemented. "
+ "No statistics will be produced."));
+ }
+ else
+ {
+ lex_error_expecting (lexer, "SCALE", "MODEL", "SUMMARY", "MISSING",
+ "STATISTICS");
+ goto error;
+ }
+ }
+
+ if (r.model == MODEL_SPLIT)
+ {
+ if (r.split_point >= r.n_vars)
+ {
+ lex_ofs_error (lexer, split_ofs, split_ofs,
+ _("The split point must be less than the "
+ "number of variables."));
+ lex_ofs_msg (lexer, SN, vars_start, vars_end,
+ ngettext ("There is %zu variable.",
+ "There are %zu variables.", r.n_vars),
+ r.n_vars);
+ goto error;
+ }
+
+ r.n_sc += 2;
+ r.sc = xrealloc (r.sc, sizeof (struct cronbach) * r.n_sc);
+
+ const struct cronbach *s = &r.sc[0];
+
+ r.sc[1].n_items = r.split_point == -1 ? s->n_items / 2 : r.split_point;
+
+ r.sc[2].n_items = s->n_items - r.sc[1].n_items;
+ r.sc[1].items = XCALLOC (r.sc[1].n_items, const struct variable *);
+ r.sc[2].items = XCALLOC (r.sc[2].n_items, const struct variable *);
+
+ size_t i = 0;
+ while (i < r.sc[1].n_items)
+ {
+ r.sc[1].items[i] = s->items[i];
+ i++;
+ }
+ while (i < s->n_items)
+ {
+ r.sc[2].items[i - r.sc[1].n_items] = s->items[i];
+ i++;
+ }
+ }
+
+ if (r.summary_total)
+ {
+ const int base_sc = r.n_sc;
+
+ r.total_start = base_sc;
+
+ r.n_sc += r.sc[0].n_items;
+ r.sc = xrealloc (r.sc, sizeof (struct cronbach) * r.n_sc);
+
+ for (size_t i = 0; i < r.sc[0].n_items; ++i)
+ {
+ struct cronbach *s = &r.sc[i + base_sc];
+
+ s->n_items = r.sc[0].n_items - 1;
+ s->items = xcalloc (s->n_items, sizeof (struct variable *));
+
+ size_t v_dest = 0;
+ for (size_t v_src = 0; v_src < r.sc[0].n_items; ++v_src)
+ if (v_src != i)
+ s->items[v_dest++] = r.sc[0].items[v_src];
+ }
+ }
+
+ if (!run_reliability (ds, &r))
+ goto error;
+
+ reliability_destroy (&r);
+ return CMD_SUCCESS;
+
+ error:
+ reliability_destroy (&r);
+ return CMD_FAILURE;
+}
+
+
+static void
+do_reliability (struct casereader *group, struct dataset *ds,
+ const struct reliability *rel);
+
+
+static void reliability_summary_total (const struct reliability *rel);
+
+static void reliability_statistics (const struct reliability *rel);
+
+
+static bool
+run_reliability (struct dataset *ds, const struct reliability *reliability)
+{
+ for (size_t si = 0; si < reliability->n_sc; ++si)
+ {
+ struct cronbach *s = &reliability->sc[si];
+
+ s->m = xcalloc (s->n_items, sizeof *s->m);
+ s->total = moments1_create (MOMENT_VARIANCE);
+
+ for (size_t i = 0; i < s->n_items; ++i)
+ s->m[i] = moments1_create (MOMENT_VARIANCE);
+ }
+
+ struct dictionary *dict = dataset_dict (ds);
+ struct casegrouper *grouper = casegrouper_create_splits (proc_open (ds), dict);
+ struct casereader *group;
+ while (casegrouper_get_next_group (grouper, &group))
+ {
+ do_reliability (group, ds, reliability);
+
+ reliability_statistics (reliability);
+
+ if (reliability->summary_total)
+ reliability_summary_total (reliability);
+ }
+
+ bool ok = casegrouper_destroy (grouper);
+ ok = proc_commit (ds) && ok;
+ return ok;
+}
+\f
+/* Return the sum of all the item variables in S */
+static double
+append_sum (const struct ccase *c, casenumber n UNUSED, void *aux)
+{
+ double sum = 0;
+ const struct cronbach *s = aux;
+
+ for (int v = 0; v < s->n_items; ++v)
+ sum += case_num (c, s->items[v]);
+
+ return sum;
+}
+
+static void
+case_processing_summary (casenumber n_valid, casenumber n_missing,
+ const struct dictionary *);
+
+static double
+alpha (int k, double sum_of_variances, double variance_of_sums)
+{
+ return k / (k - 1.0) * (1 - sum_of_variances / variance_of_sums);
+}
+
+static void
+do_reliability (struct casereader *input, struct dataset *ds,
+ const struct reliability *rel)
+{
+ for (size_t si = 0; si < rel->n_sc; ++si)
+ {
+ struct cronbach *s = &rel->sc[si];
+
+ moments1_clear (s->total);
+ for (size_t i = 0; i < s->n_items; ++i)
+ moments1_clear (s->m[i]);
+ }
+
+ casenumber n_missing;
+ input = casereader_create_filter_missing (input,
+ rel->vars,
+ rel->n_vars,
+ rel->exclude,
+ &n_missing,
+ NULL);
+
+ for (size_t si = 0; si < rel->n_sc; ++si)
+ {
+ struct cronbach *s = &rel->sc[si];
+ s->totals_idx = caseproto_get_n_widths (casereader_get_proto (input));
+ input = casereader_create_append_numeric (input, append_sum, s, NULL);
+ }
+
+ struct ccase *c;
+ casenumber n_valid = 0;
+ for (; (c = casereader_read (input)) != NULL; case_unref (c))
+ {
+ double weight = 1.0;
+ n_valid++;
+
+ for (size_t si = 0; si < rel->n_sc; ++si)
+ {
+ struct cronbach *s = &rel->sc[si];
+
+ for (size_t i = 0; i < s->n_items; ++i)
+ moments1_add (s->m[i], case_num (c, s->items[i]), weight);
+ moments1_add (s->total, case_num_idx (c, s->totals_idx), weight);
+ }
+ }
+ casereader_destroy (input);
+
+ for (size_t si = 0; si < rel->n_sc; ++si)
+ {
+ struct cronbach *s = &rel->sc[si];
+
+ s->sum_of_variances = 0;
+ for (size_t i = 0; i < s->n_items; ++i)
+ {
+ double weight, mean, variance;
+ moments1_calculate (s->m[i], &weight, &mean, &variance, NULL, NULL);
+
+ s->sum_of_variances += variance;
+ }
+
+ moments1_calculate (s->total, NULL, NULL, &s->variance_of_sums,
+ NULL, NULL);
+
+ s->alpha = alpha (s->n_items, s->sum_of_variances, s->variance_of_sums);
+ }
+
+ output_item_submit (text_item_create_nocopy (
+ TEXT_ITEM_TITLE,
+ xasprintf (_("Scale: %s"), rel->scale_name),
+ NULL));
+
+ case_processing_summary (n_valid, n_missing, dataset_dict (ds));
+}
+
+static void
+case_processing_summary (casenumber n_valid, casenumber n_missing,
+ const struct dictionary *dict)
+{
+ struct pivot_table *table = pivot_table_create (
+ N_("Case Processing Summary"));
+ pivot_table_set_weight_var (table, dict_get_weight (dict));
+
+ pivot_dimension_create (table, PIVOT_AXIS_COLUMN, N_("Statistics"),
+ N_("N"), PIVOT_RC_COUNT,
+ N_("Percent"), PIVOT_RC_PERCENT);
+
+ struct pivot_dimension *cases = pivot_dimension_create (
+ table, PIVOT_AXIS_ROW, N_("Cases"), N_("Valid"), N_("Excluded"),
+ N_("Total"));
+ cases->root->show_label = true;
+
+ casenumber total = n_missing + n_valid;
+
+ struct entry
+ {
+ int stat_idx;
+ int case_idx;
+ double x;
+ }
+ entries[] = {
+ { 0, 0, n_valid },
+ { 0, 1, n_missing },
+ { 0, 2, total },
+ { 1, 0, 100.0 * n_valid / total },
+ { 1, 1, 100.0 * n_missing / total },
+ { 1, 2, 100.0 }
+ };
+
+ for (size_t i = 0; i < sizeof entries / sizeof *entries; i++)
+ {
+ const struct entry *e = &entries[i];
+ pivot_table_put2 (table, e->stat_idx, e->case_idx,
+ pivot_value_new_number (e->x));
+ }
+
+ pivot_table_submit (table);
+}
+
+static void
+reliability_summary_total (const struct reliability *rel)
+{
+ struct pivot_table *table = pivot_table_create (N_("Item-Total Statistics"));
+
+ pivot_dimension_create (table, PIVOT_AXIS_COLUMN, N_("Statistics"),
+ N_("Scale Mean if Item Deleted"),
+ N_("Scale Variance if Item Deleted"),
+ N_("Corrected Item-Total Correlation"),
+ N_("Cronbach's Alpha if Item Deleted"));
+
+ struct pivot_dimension *variables = pivot_dimension_create (
+ table, PIVOT_AXIS_ROW, N_("Variables"));
+
+ for (size_t i = 0; i < rel->sc[0].n_items; ++i)
+ {
+ const struct cronbach *s = &rel->sc[rel->total_start + i];
+
+ int var_idx = pivot_category_create_leaf (
+ variables->root, pivot_value_new_variable (rel->sc[0].items[i]));
+
+ double mean;
+ moments1_calculate (s->total, NULL, &mean, NULL, NULL, NULL);
+
+ double var;
+ moments1_calculate (rel->sc[0].m[i], NULL, NULL, &var, NULL, NULL);
+ double cov
+ = (rel->sc[0].variance_of_sums + var - s->variance_of_sums) / 2.0;
+
+ double entries[] = {
+ mean,
+ s->variance_of_sums,
+ (cov - var) / sqrt (var * s->variance_of_sums),
+ s->alpha,
+ };
+ 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);
+}
+
+
+static void
+reliability_statistics (const struct reliability *rel)
+{
+ struct pivot_table *table = pivot_table_create (
+ N_("Reliability Statistics"));
+ pivot_table_set_weight_var (table, rel->wv);
+
+ if (rel->model == MODEL_ALPHA)
+ {
+ pivot_dimension_create (table, PIVOT_AXIS_COLUMN,
+ N_("Statistics"),
+ N_("Cronbach's Alpha"), PIVOT_RC_OTHER,
+ N_("N of Items"), PIVOT_RC_COUNT);
+
+ const struct cronbach *s = &rel->sc[0];
+ pivot_table_put1 (table, 0, pivot_value_new_number (s->alpha));
+ pivot_table_put1 (table, 1, pivot_value_new_number (s->n_items));
+ }
+ else
+ {
+ struct pivot_dimension *statistics = pivot_dimension_create (
+ table, PIVOT_AXIS_ROW, N_("Statistics"));
+ struct pivot_category *alpha = pivot_category_create_group (
+ statistics->root, N_("Cronbach's Alpha"));
+ pivot_category_create_group (alpha, N_("Part 1"),
+ N_("Value"), PIVOT_RC_OTHER,
+ N_("N of Items"), PIVOT_RC_COUNT);
+ pivot_category_create_group (alpha, N_("Part 2"),
+ N_("Value"), PIVOT_RC_OTHER,
+ N_("N of Items"), PIVOT_RC_COUNT);
+ pivot_category_create_leaves (alpha,
+ N_("Total N of Items"), PIVOT_RC_COUNT);
+ pivot_category_create_leaves (statistics->root,
+ N_("Correlation Between Forms"),
+ PIVOT_RC_OTHER);
+ pivot_category_create_group (statistics->root,
+ N_("Spearman-Brown Coefficient"),
+ N_("Equal Length"), PIVOT_RC_OTHER,
+ N_("Unequal Length"), PIVOT_RC_OTHER);
+ pivot_category_create_leaves (statistics->root,
+ N_("Guttman Split-Half Coefficient"),
+ PIVOT_RC_OTHER);
+
+ /* R is the correlation between the two parts */
+ double r0 = rel->sc[0].variance_of_sums -
+ rel->sc[1].variance_of_sums -
+ rel->sc[2].variance_of_sums;
+ double r1 = (r0 / sqrt (rel->sc[1].variance_of_sums)
+ / sqrt (rel->sc[2].variance_of_sums)
+ / 2.0);
+
+ /* Guttman Split Half Coefficient */
+ double g = 2 * r0 / rel->sc[0].variance_of_sums;
+
+ double tmp = (1.0 - r1*r1) * rel->sc[1].n_items * rel->sc[2].n_items /
+ pow2 (rel->sc[0].n_items);
+
+ double entries[] = {
+ rel->sc[1].alpha,
+ rel->sc[1].n_items,
+ rel->sc[2].alpha,
+ rel->sc[2].n_items,
+ rel->sc[1].n_items + rel->sc[2].n_items,
+ r1,
+ 2 * r1 / (1.0 + r1),
+ (sqrt (pow4 (r1) + 4 * pow2 (r1) * tmp) - pow2 (r1)) / (2 * tmp),
+ g,
+ };
+ for (size_t i = 0; i < sizeof entries / sizeof *entries; i++)
+ pivot_table_put1 (table, i, pivot_value_new_number (entries[i]));
+ }
+
+ pivot_table_submit (table);
+}
projects / pspp / blobdiff