/* PSPP - One way ANOVA. -*-c-*-
- Copyright (C) 1997-9, 2000 Free Software Foundation, Inc.
- Author: John Darrington 2004
+Copyright (C) 1997-9, 2000 Free Software Foundation, Inc.
+Author: John Darrington 2004
- 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 2 of the
- License, or (at your option) any later version.
+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 2 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.
+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, write to the Free Software
- Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA
- 02111-1307, USA. */
+You should have received a copy of the GNU General Public License
+along with this program; if not, write to the Free Software
+Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA
+02110-1301, USA. */
#include <config.h>
#include <gsl/gsl_cdf.h>
#include "alloc.h"
#include "str.h"
#include "case.h"
+#include "dictionary.h"
#include "command.h"
#include "lexer.h"
#include "error.h"
#include "vfm.h"
#include "hash.h"
#include "casefile.h"
+#include "group_proc.h"
+#include "group.h"
#include "levene.h"
+/* (headers) */
/* (specification)
"ONEWAY" (oneway_):
- *variables=custom;
- +missing=miss:!analysis/listwise,
- incl:include/!exclude;
- contrast= double list;
- statistics[st_]=descriptives,homogeneity.
+ *^variables=custom;
+ +missing=miss:!analysis/listwise,
+ incl:include/!exclude;
+ contrast= double list;
+ statistics[st_]=descriptives,homogeneity.
*/
/* (declarations) */
/* (functions) */
+static int bad_weight_warn = 1;
+
+
static struct cmd_oneway cmd;
/* The independent variable */
static struct variable *indep_var;
-/* A hash of the values of the independent variable */
-struct hsh_table *ind_vals;
-
-/* Number of factors (groups) */
-static int n_groups;
-
/* Number of dependent variables */
static int n_vars;
static struct variable **vars;
+/* A hash table containing all the distinct values of the independent
+ variables */
+static struct hsh_table *global_group_hash ;
+/* The number of distinct values of the independent variable, when all
+ missing values are disregarded */
+static int ostensible_number_of_groups=-1;
/* Function to use for testing for missing values */
static is_missing_func value_is_missing;
-static void calculate(const struct casefile *cf, void *_mode);
+static void run_oneway(const struct casefile *cf, void *_mode);
/* Routines to show the output tables */
static void show_anova_table(void);
static void show_descriptives(void);
static void show_homogeneity(void);
-static void show_contrast_coeffs(void);
-static void show_contrast_tests(void);
+
+static void show_contrast_coeffs(short *);
+static void show_contrast_tests(short *);
+enum stat_table_t {STAT_DESC = 1, STAT_HOMO = 2};
+
+static enum stat_table_t stat_tables ;
+
+void output_oneway(void);
+
int
cmd_oneway(void)
else
value_is_missing = is_missing;
- multipass_procedure_with_splits (calculate, &cmd);
+ /* What statistics were requested */
+ if ( cmd.sbc_statistics )
+ {
+
+ for (i = 0 ; i < ONEWAY_ST_count ; ++i )
+ {
+ if ( ! cmd.a_statistics[i] ) continue;
+
+ switch (i) {
+ case ONEWAY_ST_DESCRIPTIVES:
+ stat_tables |= STAT_DESC;
+ break;
+ case ONEWAY_ST_HOMOGENEITY:
+ stat_tables |= STAT_HOMO;
+ break;
+ }
+ }
+ }
+
+ multipass_procedure_with_splits (run_oneway, &cmd);
+
+ free (vars);
+ free_oneway (&cmd);
+
+ return CMD_SUCCESS;
+}
+
+
+void
+output_oneway(void)
+{
+
+ int i;
+ short *bad_contrast ;
+
+ bad_contrast = xmalloc ( sizeof (short) * cmd.sbc_contrast );
/* Check the sanity of the given contrast values */
for (i = 0 ; i < cmd.sbc_contrast ; ++i )
int j;
double sum = 0;
- if ( subc_list_double_count(&cmd.dl_contrast[i]) != n_groups )
+ bad_contrast[i] = 0;
+ if ( subc_list_double_count(&cmd.dl_contrast[i]) !=
+ ostensible_number_of_groups )
{
- msg(SE, _("Number of contrast coefficients must equal the number of groups"));
- return CMD_FAILURE;
+ msg(SW,
+ _("Number of contrast coefficients must equal the number of groups"));
+ bad_contrast[i] = 1;
+ continue;
}
- for (j=0; j < n_groups ; ++j )
+ for (j=0; j < ostensible_number_of_groups ; ++j )
sum += subc_list_double_at(&cmd.dl_contrast[i],j);
if ( sum != 0.0 )
msg(SW,_("Coefficients for contrast %d do not total zero"),i + 1);
}
+ if ( stat_tables & STAT_DESC )
+ show_descriptives();
- /* Show the statistics tables */
- if ( cmd.sbc_statistics )
- {
- for (i = 0 ; i < ONEWAY_ST_count ; ++i )
- {
- if ( ! cmd.a_statistics[i] ) continue;
-
- switch (i) {
- case ONEWAY_ST_DESCRIPTIVES:
- show_descriptives();
- break;
- case ONEWAY_ST_HOMOGENEITY:
- show_homogeneity();
- break;
- }
-
- }
- }
+ if ( stat_tables & STAT_HOMO )
+ show_homogeneity();
show_anova_table();
- if (cmd.sbc_contrast)
+ if (cmd.sbc_contrast )
{
- show_contrast_coeffs();
- show_contrast_tests();
+ show_contrast_coeffs(bad_contrast);
+ show_contrast_tests(bad_contrast);
}
- hsh_destroy(ind_vals);
- return CMD_SUCCESS;
-}
+ free(bad_contrast);
+
+ /* Clean up */
+ for (i = 0 ; i < n_vars ; ++i )
+ {
+ struct hsh_table *group_hash = group_proc_get (vars[i])->group_hash;
+
+ hsh_destroy(group_hash);
+ }
+ hsh_destroy(global_group_hash);
+
+}
for ( i=0 ; i < n_vars ; ++i )
{
- char *s = (vars[i]->label) ? vars[i]->label : vars[i]->name;
+ struct group_statistics *totals = &group_proc_get (vars[i])->ugs;
+ struct hsh_table *group_hash = group_proc_get (vars[i])->group_hash;
+ struct hsh_iterator g;
+ struct group_statistics *gs;
+ double ssa=0;
+ const char *s = var_to_string(vars[i]);
+
+ for (gs = hsh_first (group_hash,&g);
+ gs != 0;
+ gs = hsh_next(group_hash,&g))
+ {
+ ssa += (gs->sum * gs->sum)/gs->n;
+ }
+
+ ssa -= ( totals->sum * totals->sum ) / totals->n ;
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"));
if (i > 0)
tab_hline(t, TAL_1, 0, n_cols - 1 , i * 3 + 1);
- }
-
-
- tab_title (t, 0, "ANOVA");
- tab_submit (t);
-
-
-}
+ {
+ struct group_proc *gp = group_proc_get (vars[i]);
+ const double sst = totals->ssq - ( totals->sum * totals->sum) / totals->n ;
+ const double df1 = gp->n_groups - 1;
+ const double df2 = totals->n - gp->n_groups ;
+ const double msa = ssa / df1;
+
+ gp->mse = (sst - ssa) / df2;
+
+
+ /* Sums of Squares */
+ tab_float (t, 2, i * 3 + 1, 0, ssa, 10, 2);
+ tab_float (t, 2, i * 3 + 3, 0, sst, 10, 2);
+ tab_float (t, 2, i * 3 + 2, 0, sst - ssa, 10, 2);
+
+
+ /* Degrees of freedom */
+ tab_float (t, 3, i * 3 + 1, 0, df1, 4, 0);
+ tab_float (t, 3, i * 3 + 2, 0, df2, 4, 0);
+ tab_float (t, 3, i * 3 + 3, 0, totals->n - 1, 4, 0);
+
+ /* Mean Squares */
+ tab_float (t, 4, i * 3 + 1, TAB_RIGHT, msa, 8, 3);
+ tab_float (t, 4, i * 3 + 2, TAB_RIGHT, gp->mse, 8, 3);
+
+
+ {
+ const double F = msa/gp->mse ;
+
+ /* The F value */
+ tab_float (t, 5, i * 3 + 1, 0, F, 8, 3);
+
+ /* The significance */
+ tab_float (t, 6, i * 3 + 1, 0, gsl_cdf_fdist_Q(F,df1,df2), 8, 3);
+ }
-static void
-calculate(const struct casefile *cf, void *cmd_)
-{
- struct casereader *r;
- struct ccase c;
-
- struct cmd_t_test *cmd = (struct cmd_t_test *) cmd_;
-
-
- ind_vals = hsh_create(4, (hsh_compare_func *) compare_values,
- (hsh_hash_func *) hash_value,
- 0, (void *) indep_var->width );
-
- for(r = casefile_get_reader (cf);
- casereader_read (r, &c) ;
- case_destroy (&c))
- {
-
- const union value *val = case_data (&c, indep_var->fv);
-
- hsh_insert(ind_vals, (void *) val);
+ }
- /*
- if (! value_is_missing(val,v) )
- {
- gs->n+=weight;
- gs->sum+=weight * val->f;
- gs->ssq+=weight * val->f * val->f;
- }
- */
-
}
- casereader_destroy (r);
- n_groups = hsh_count(ind_vals);
+ tab_title (t, 0, _("ANOVA"));
+ tab_submit (t);
}
-
/* Show the descriptives table */
static void
show_descriptives(void)
{
int v;
int n_cols =10;
- int n_rows = n_vars * (n_groups + 1 )+ 2;
-
struct tab_table *t;
+ int row;
+
+ const double confidence=0.95;
+ const double q = (1.0 - confidence) / 2.0;
+
+ int n_rows = 2 ;
+
+ for ( v = 0 ; v < n_vars ; ++v )
+ n_rows += group_proc_get (vars[v])->n_groups + 1;
t = tab_create (n_cols,n_rows,0);
tab_headers (t, 2, 0, 2, 0);
tab_vline(t, TAL_0, 7, 0, 0);
tab_hline(t, TAL_1, 6, 7, 1);
- tab_joint_text (t, 6, 0, 7, 0, TAB_CENTER | TAT_TITLE, _("95% Confidence Interval for Mean"));
+ tab_joint_text (t, 6, 0, 7, 0, TAB_CENTER | TAT_TITLE | TAT_PRINTF, _("%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, 9, 1, TAB_CENTER | TAT_TITLE, _("Maximum"));
- tab_title (t, 0, "Descriptives");
+ tab_title (t, 0, _("Descriptives"));
+ row = 2;
for ( v=0 ; v < n_vars ; ++v )
{
- struct hsh_iterator g;
- union value *group_value;
- int count = 0 ;
- char *s = (vars[v]->label) ? vars[v]->label : vars[v]->name;
+ double T;
+ double std_error;
+
+ struct group_proc *gp = group_proc_get (vars[v]);
- tab_text (t, 0, v * ( n_groups + 1 ) + 2, TAB_LEFT | TAT_TITLE, s);
- if ( v > 0)
- tab_hline(t, TAL_1, 0, n_cols - 1 , v * (n_groups + 1) + 2);
+ struct group_statistics *gs;
+ struct group_statistics *totals = &gp->ugs;
+
+ const char *s = var_to_string(vars[v]);
+ struct group_statistics **gs_array = hsh_sort(gp->group_hash);
+ int count = 0;
+
+ tab_text (t, 0, row, TAB_LEFT | TAT_TITLE, s);
+ if ( v > 0)
+ tab_hline(t, TAL_1, 0, n_cols - 1 , row);
- for (group_value = hsh_first (ind_vals,&g);
- group_value != 0;
- group_value = hsh_next(ind_vals,&g))
+ for (count = 0 ; count < hsh_count(gp->group_hash) ; ++count)
{
- char *lab;
+ gs = gs_array[count];
- lab = val_labs_find(indep_var->val_labs,*group_value);
-
- if ( lab )
- tab_text (t, 1, v * (n_groups + 1)+ count + 2,
- TAB_LEFT | TAT_TITLE ,lab);
- else
- tab_text (t, 1, v * (n_groups + 1) + count + 2,
- TAB_LEFT | TAT_TITLE | TAT_PRINTF, "%g", group_value->f);
+ tab_text (t, 1, row + count,
+ TAB_LEFT | TAT_TITLE ,value_to_string(&gs->id,indep_var));
+
+ /* Now fill in the numbers ... */
+
+ tab_float (t, 2, row + count, 0, gs->n, 8,0);
+
+ tab_float (t, 3, row + count, 0, gs->mean,8,2);
- count++ ;
+ tab_float (t, 4, row + count, 0, gs->std_dev,8,2);
+
+ std_error = gs->std_dev/sqrt(gs->n) ;
+ tab_float (t, 5, row + count, 0,
+ std_error, 8,2);
+
+ /* Now the confidence interval */
+
+ T = gsl_cdf_tdist_Qinv(q,gs->n - 1);
+
+ tab_float(t, 6, row + count, 0,
+ gs->mean - T * std_error, 8, 2);
+
+ tab_float(t, 7, row + count, 0,
+ gs->mean + T * std_error, 8, 2);
+
+ /* Min and Max */
+
+ tab_float(t, 8, row + count, 0, gs->minimum, 8, 2);
+ tab_float(t, 9, row + count, 0, gs->maximum, 8, 2);
+
}
- tab_text (t, 1, v * (n_groups + 1)+ count + 2,
- TAB_LEFT | TAT_TITLE ,_("Total"));
+ tab_text (t, 1, row + count,
+ TAB_LEFT | TAT_TITLE ,_("Total"));
+
+ tab_float (t, 2, row + count, 0, totals->n, 8,0);
+
+ tab_float (t, 3, row + count, 0, totals->mean, 8,2);
+
+ tab_float (t, 4, row + count, 0, totals->std_dev,8,2);
+
+ std_error = totals->std_dev/sqrt(totals->n) ;
+
+ tab_float (t, 5, row + count, 0, std_error, 8,2);
+
+ /* Now the confidence interval */
+ T = gsl_cdf_tdist_Qinv(q,totals->n - 1);
+
+ tab_float(t, 6, row + count, 0,
+ totals->mean - T * std_error, 8, 2);
+
+ tab_float(t, 7, row + count, 0,
+ totals->mean + T * std_error, 8, 2);
+ /* Min and Max */
+
+ tab_float(t, 8, row + count, 0, totals->minimum, 8, 2);
+ tab_float(t, 9, row + count, 0, totals->maximum, 8, 2);
+
+ row += gp->n_groups + 1;
}
}
-
/* Show the homogeneity table */
static void
show_homogeneity(void)
for ( v=0 ; v < n_vars ; ++v )
{
- char *s = (vars[v]->label) ? vars[v]->label : vars[v]->name;
+ double F;
+ const struct variable *var = vars[v];
+ const struct group_proc *gp = group_proc_get (vars[v]);
+ const char *s = var_to_string(var);
+ const struct group_statistics *totals = &gp->ugs;
+
+ const double df1 = gp->n_groups - 1;
+ const double df2 = totals->n - gp->n_groups ;
tab_text (t, 0, v + 1, TAB_LEFT | TAT_TITLE, s);
+
+ F = gp->levene;
+ tab_float (t, 1, v + 1, TAB_RIGHT, F, 8,3);
+ tab_float (t, 2, v + 1, TAB_RIGHT, df1 ,8,0);
+ tab_float (t, 3, v + 1, TAB_RIGHT, df2 ,8,0);
+
+ /* Now the significance */
+ tab_float (t, 4, v + 1, TAB_RIGHT,gsl_cdf_fdist_Q(F,df1,df2), 8, 3);
}
tab_submit (t);
/* Show the contrast coefficients table */
static void
-show_contrast_coeffs(void)
+show_contrast_coeffs(short *bad_contrast)
{
- char *s;
- int n_cols = 2 + n_groups;
+ int n_cols = 2 + ostensible_number_of_groups;
int n_rows = 2 + cmd.sbc_contrast;
- struct hsh_iterator g;
union value *group_value;
int count = 0 ;
-
+ void **group_values ;
struct tab_table *t;
-
t = tab_create (n_cols,n_rows,0);
tab_headers (t, 2, 0, 2, 0);
tab_dim (t, tab_natural_dimensions);
0, 0,
n_cols - 1, n_rows - 1);
-
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_vline(t, TAL_2, 2, 0, n_rows - 1);
tab_title (t, 0, _("Contrast Coefficients"));
tab_text (t, 0, 2, TAB_LEFT | TAT_TITLE, _("Contrast"));
- s = (indep_var->label) ? indep_var->label : indep_var->name;
- tab_joint_text (t, 2, 0, n_cols - 1, 0, TAB_CENTER | TAT_TITLE, s);
+ tab_joint_text (t, 2, 0, n_cols - 1, 0, TAB_CENTER | TAT_TITLE,
+ var_to_string(indep_var));
- for (group_value = hsh_first (ind_vals,&g);
- group_value != 0;
- group_value = hsh_next(ind_vals,&g))
+ group_values = hsh_sort(global_group_hash);
+ for (count = 0 ;
+ count < hsh_count(global_group_hash) ;
+ ++count)
{
int i;
- char *lab;
+ group_value = group_values[count];
- lab = val_labs_find(indep_var->val_labs,*group_value);
-
- if ( lab )
- tab_text (t, count + 2, 1,
- TAB_CENTER | TAT_TITLE ,lab);
- else
- tab_text (t, count + 2, 1,
- TAB_CENTER | TAT_TITLE | TAT_PRINTF, "%g", group_value->f);
+ tab_text (t, count + 2, 1, TAB_CENTER | TAT_TITLE,
+ value_to_string(group_value, indep_var));
for (i = 0 ; i < cmd.sbc_contrast ; ++i )
{
tab_text(t, 1, i + 2, TAB_CENTER | TAT_PRINTF, "%d", i + 1);
- tab_text(t, count + 2, i + 2, TAB_RIGHT | TAT_PRINTF, "%g",
- subc_list_double_at(&cmd.dl_contrast[i],count)
- );
+
+ if ( bad_contrast[i] )
+ tab_text(t, count + 2, i + 2, TAB_RIGHT, "?" );
+ else
+ tab_text(t, count + 2, i + 2, TAB_RIGHT | TAT_PRINTF, "%g",
+ subc_list_double_at(&cmd.dl_contrast[i], count)
+ );
}
-
- count++ ;
}
-
+
tab_submit (t);
-
}
-
/* Show the results of the contrast tests */
static void
-show_contrast_tests(void)
+show_contrast_tests(short *bad_contrast)
{
int v;
int n_cols = 8;
0, 0,
n_cols - 1, n_rows - 1);
-
tab_box (t,
-1,-1,
TAL_0, TAL_0,
int i;
int lines_per_variable = 2 * cmd.sbc_contrast;
+
tab_text (t, 0, (v * lines_per_variable) + 1, TAB_LEFT | TAT_TITLE,
- vars[v]->label?vars[v]->label:vars[v]->name);
+ var_to_string(vars[v]));
for ( i = 0 ; i < cmd.sbc_contrast ; ++i )
{
- tab_text (t, 1, (v * lines_per_variable) + i*2 + 1,
- TAB_LEFT | TAT_TITLE,
- _("Assume equal variances"));
+ int ci;
+ double contrast_value = 0.0;
+ double coef_msq = 0.0;
+ struct group_proc *grp_data = group_proc_get (vars[v]);
+ struct hsh_table *group_hash = grp_data->group_hash;
+
+ void **group_stat_array;
+
+ 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!!
+ The following formula may help to understand it:
+ \frac{\left(\sum_{i=1}^k{c_i^2\frac{s_i^2}{n_i}}\right)^2}
+ {
+ \sum_{i=1}^k\left(
+ \frac{\left(c_i^2\frac{s_i^2}{n_i}\right)^2} {n_i-1}
+ \right)
+ }
+ */
- tab_text (t, 1, (v * lines_per_variable) + i*2 + 2,
- TAB_LEFT | TAT_TITLE,
- _("Does not assume equal"));
+ double df_denominator = 0.0;
+ double df_numerator = 0.0;
+ if ( i == 0 )
+ {
+ 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 + cmd.sbc_contrast,
+ TAB_LEFT | TAT_TITLE,
+ _("Does not assume equal"));
+ }
- tab_text (t, 2, (v * lines_per_variable) + i*2 + 1,
+ tab_text (t, 2, (v * lines_per_variable) + i + 1,
TAB_CENTER | TAT_TITLE | TAT_PRINTF, "%d",i+1);
- tab_text (t, 2, (v * lines_per_variable) + i*2 + 2,
+
+ tab_text (t, 2, (v * lines_per_variable) + i + 1 + cmd.sbc_contrast,
TAB_CENTER | TAT_TITLE | TAT_PRINTF, "%d",i+1);
+
+ if ( bad_contrast[i])
+ continue;
+
+ group_stat_array = hsh_sort(group_hash);
+
+ for (ci = 0 ; ci < hsh_count(group_hash) ; ++ci)
+ {
+ const double coef = subc_list_double_at(&cmd.dl_contrast[i], ci);
+ struct group_statistics *gs = group_stat_array[ci];
+
+ const double winv = (gs->std_dev * gs->std_dev) / gs->n;
+
+ contrast_value += coef * gs->mean;
+
+ coef_msq += (coef * coef) / gs->n ;
+
+ sec_vneq += (coef * coef) * (gs->std_dev * gs->std_dev ) /gs->n ;
+
+ df_numerator += (coef * coef) * winv;
+ df_denominator += pow2((coef * coef) * winv) / (gs->n - 1);
+ }
+ sec_vneq = sqrt(sec_vneq);
+
+ df_numerator = pow2(df_numerator);
+
+ tab_float (t, 3, (v * lines_per_variable) + i + 1,
+ TAB_RIGHT, contrast_value, 8,2);
+
+ tab_float (t, 3, (v * lines_per_variable) + i + 1 +
+ cmd.sbc_contrast,
+ TAB_RIGHT, contrast_value, 8,2);
+
+ std_error_contrast = sqrt(grp_data->mse * coef_msq);
+
+ /* Std. Error */
+ tab_float (t, 4, (v * lines_per_variable) + i + 1,
+ TAB_RIGHT, std_error_contrast,
+ 8,3);
+
+ T = fabs(contrast_value / std_error_contrast) ;
+
+ /* T Statistic */
+
+ tab_float (t, 5, (v * lines_per_variable) + i + 1,
+ TAB_RIGHT, T,
+ 8,3);
+
+ df = grp_data->ugs.n - grp_data->n_groups;
+
+ /* Degrees of Freedom */
+ tab_float (t, 6, (v * lines_per_variable) + i + 1,
+ TAB_RIGHT, df,
+ 8,0);
+
+
+ /* Significance TWO TAILED !!*/
+ tab_float (t, 7, (v * lines_per_variable) + i + 1,
+ TAB_RIGHT, 2 * gsl_cdf_tdist_Q(T,df),
+ 8,3);
+
+
+ /* Now for the Variances NOT Equal case */
+
+ /* Std. Error */
+ tab_float (t, 4,
+ (v * lines_per_variable) + i + 1 + cmd.sbc_contrast,
+ TAB_RIGHT, sec_vneq,
+ 8,3);
+
+
+ T = contrast_value / sec_vneq;
+ tab_float (t, 5,
+ (v * lines_per_variable) + i + 1 + cmd.sbc_contrast,
+ TAB_RIGHT, T,
+ 8,3);
+
+
+ df = df_numerator / df_denominator;
+
+ tab_float (t, 6,
+ (v * lines_per_variable) + i + 1 + cmd.sbc_contrast,
+ TAB_RIGHT, df,
+ 8,3);
+
+ /* The Significance */
+
+ tab_float (t, 7, (v * lines_per_variable) + i + 1 + cmd.sbc_contrast,
+ TAB_RIGHT, 2 * gsl_cdf_tdist_Q(T,df),
+ 8,3);
+
+
}
if ( v > 0 )
tab_submit (t);
}
+
+
+/* ONEWAY ANOVA Calculations */
+
+static void postcalc ( struct cmd_oneway *cmd UNUSED );
+
+static void precalc ( struct cmd_oneway *cmd UNUSED );
+
+
+
+/* Pre calculations */
+static void
+precalc ( struct cmd_oneway *cmd UNUSED )
+{
+ int i=0;
+
+ for(i=0; i< n_vars ; ++i)
+ {
+ struct group_proc *gp = group_proc_get (vars[i]);
+ struct group_statistics *totals = &gp->ugs;
+
+ /* Create a hash for each of the dependent variables.
+ The hash contains a group_statistics structure,
+ and is keyed by value of the independent variable */
+
+ gp->group_hash =
+ hsh_create(4,
+ (hsh_compare_func *) compare_group,
+ (hsh_hash_func *) hash_group,
+ (hsh_free_func *) free_group,
+ (void *) indep_var->width );
+
+
+ totals->sum=0;
+ totals->n=0;
+ totals->ssq=0;
+ totals->sum_diff=0;
+ totals->maximum = - DBL_MAX;
+ totals->minimum = DBL_MAX;
+ }
+}
+
+
+static void
+run_oneway(const struct casefile *cf, void *cmd_)
+{
+ struct casereader *r;
+ struct ccase c;
+
+ struct cmd_oneway *cmd = (struct cmd_oneway *) cmd_;
+
+ global_group_hash = hsh_create(4,
+ (hsh_compare_func *) compare_values,
+ (hsh_hash_func *) hash_value,
+ 0,
+ (void *) indep_var->width );
+ precalc(cmd);
+
+ for(r = casefile_get_reader (cf);
+ casereader_read (r, &c) ;
+ case_destroy (&c))
+ {
+ int i;
+
+ const double weight =
+ dict_get_case_weight(default_dict,&c,&bad_weight_warn);
+
+ const union value *indep_val = case_data (&c, indep_var->fv);
+
+ /* Deal with missing values */
+ if ( value_is_missing(indep_val,indep_var) )
+ continue;
+
+ /* Skip the entire case if /MISSING=LISTWISE is set */
+ if ( cmd->miss == ONEWAY_LISTWISE )
+ {
+ for(i = 0; i < n_vars ; ++i)
+ {
+ const struct variable *v = vars[i];
+ const union value *val = case_data (&c, v->fv);
+
+ if (value_is_missing(val,v) )
+ break;
+ }
+ if ( i != n_vars )
+ continue;
+
+ }
+
+
+ hsh_insert ( global_group_hash, (void *) indep_val );
+
+ for ( i = 0 ; i < n_vars ; ++i )
+ {
+ const struct variable *v = vars[i];
+
+ const union value *val = case_data (&c, v->fv);
+
+ struct group_proc *gp = group_proc_get (vars[i]);
+ struct hsh_table *group_hash = gp->group_hash;
+
+ struct group_statistics *gs;
+
+ gs = hsh_find(group_hash, (void *) indep_val );
+
+ if ( ! gs )
+ {
+ gs = (struct group_statistics *)
+ xmalloc (sizeof(struct group_statistics));
+
+ gs->id = *indep_val;
+ gs->sum=0;
+ gs->n=0;
+ gs->ssq=0;
+ gs->sum_diff=0;
+ gs->minimum = DBL_MAX;
+ gs->maximum = -DBL_MAX;
+
+ hsh_insert ( group_hash, (void *) gs );
+ }
+
+ if (! value_is_missing(val,v) )
+ {
+ struct group_statistics *totals = &gp->ugs;
+
+ totals->n+=weight;
+ totals->sum+=weight * val->f;
+ totals->ssq+=weight * val->f * val->f;
+
+ if ( val->f * weight < totals->minimum )
+ totals->minimum = val->f * weight;
+
+ if ( val->f * weight > totals->maximum )
+ totals->maximum = val->f * weight;
+
+ gs->n+=weight;
+ gs->sum+=weight * val->f;
+ gs->ssq+=weight * val->f * val->f;
+
+ if ( val->f * weight < gs->minimum )
+ gs->minimum = val->f * weight;
+
+ if ( val->f * weight > gs->maximum )
+ gs->maximum = val->f * weight;
+ }
+
+ gp->n_groups = hsh_count ( group_hash );
+ }
+
+ }
+ casereader_destroy (r);
+
+ postcalc(cmd);
+
+
+ if ( stat_tables & STAT_HOMO )
+ levene(cf, indep_var, n_vars, vars,
+ (cmd->miss == ONEWAY_LISTWISE) ? LEV_LISTWISE : LEV_ANALYSIS ,
+ value_is_missing);
+
+ ostensible_number_of_groups = hsh_count (global_group_hash);
+
+
+ output_oneway();
+
+
+}
+
+
+/* Post calculations for the ONEWAY command */
+void
+postcalc ( struct cmd_oneway *cmd UNUSED )
+{
+ int i=0;
+
+
+ for(i = 0; i < n_vars ; ++i)
+ {
+ struct group_proc *gp = group_proc_get (vars[i]);
+ struct hsh_table *group_hash = gp->group_hash;
+ struct group_statistics *totals = &gp->ugs;
+
+ struct hsh_iterator g;
+ struct group_statistics *gs;
+
+ for (gs = hsh_first (group_hash,&g);
+ gs != 0;
+ gs = hsh_next(group_hash,&g))
+ {
+ gs->mean=gs->sum / gs->n;
+ gs->s_std_dev= sqrt(
+ ( (gs->ssq / gs->n ) - gs->mean * gs->mean )
+ ) ;
+
+ gs->std_dev= sqrt(
+ gs->n/(gs->n-1) *
+ ( (gs->ssq / gs->n ) - gs->mean * gs->mean )
+ ) ;
+
+ gs->se_mean = gs->std_dev / sqrt(gs->n);
+ gs->mean_diff= gs->sum_diff / gs->n;
+
+ }
+
+
+
+ totals->mean = totals->sum / totals->n;
+ totals->std_dev= sqrt(
+ totals->n/(totals->n-1) *
+ ( (totals->ssq / totals->n ) - totals->mean * totals->mean )
+ ) ;
+
+ totals->se_mean = totals->std_dev / sqrt(totals->n);
+
+ }
+}
projects / pspp-builds.git / blobdiff