02111-1307, USA. */
#include <config.h>
-#include <assert.h>
+#include <gsl/gsl_cdf.h>
+#include "error.h"
#include <stdio.h>
#include <stdlib.h>
#include <math.h>
#include "alloc.h"
#include "str.h"
-#include "dcdflib/cdflib.h"
#include "command.h"
#include "lexer.h"
#include "error.h"
#include "magic.h"
+#include "misc.h"
#include "tab.h"
#include "som.h"
#include "value-labels.h"
#include "var.h"
#include "vfm.h"
-#include "pool.h"
+#include "hash.h"
+#include "t-test.h"
+#include "casefile.h"
+#include "levene.h"
/* (specification)
"T-TEST" (tts_):
- groups=custom;
- testval=double;
+ +groups=custom;
+ +testval=double;
variables=varlist("PV_NO_SCRATCH | PV_NUMERIC");
pairs=custom;
+missing=miss:!analysis/listwise,
/* (declarations) */
/* (functions) */
-static struct cmd_t_test cmd;
-static struct pool *t_test_pool ;
+
+/* Function to use for testing for missing values */
+static is_missing_func value_is_missing;
/* Variable for the GROUPS subcommand, if given. */
-static struct variable *groups;
+static struct variable *indep_var;
/* GROUPS: Number of values specified by the user; the values
specified if any. */
-static int n_groups_values;
+
+static int n_group_values;
static union value groups_values[2];
+static enum comparison criteria[2];
+
+
/* PAIRS: Number of pairs to be compared ; each pair. */
-static int n_pairs ;
-typedef struct variable *pair_t[2] ;
-static pair_t *pairs;
+static int n_pairs = 0 ;
+struct pair
+{
+ /* The variables comprising the pair */
+ struct variable *v[2];
+ /* The number of valid variable pairs */
+ double n;
-static int parse_value (union value * v, int type) ;
+ /* The sum of the members */
+ double sum[2];
+
+ /* sum of squares of the members */
+ double ssq[2];
+
+ /* Std deviation of the members */
+ double std_dev[2];
+
+
+ /* Sample Std deviation of the members */
+ double s_std_dev[2];
+
+ /* The means of the members */
+ double mean[2];
+
+ /* The correlation coefficient between the variables */
+ double correlation;
+ /* The sum of the differences */
+ double sum_of_diffs;
+
+ /* The sum of the products */
+ double sum_of_prod;
+
+ /* The mean of the differences */
+ double mean_diff;
+
+ /* The sum of the squares of the differences */
+ double ssq_diffs;
+
+ /* The std deviation of the differences */
+ double std_dev_diff;
+};
+
+static struct pair *pairs=0;
+
+static int parse_value (union value * v, int type) ;
/* Structures and Functions for the Statistics Summary Box */
struct ssbox;
/* Submit and destroy a ssbox */
void ssbox_finalize(struct ssbox *ssb);
+/* A function to create, populate and submit the Paired Samples Correlation
+ box */
+void pscbox(void);
/* Structures and Functions for the Test Results Box */
T_PAIRED
};
+
+static int common_calc (const struct ccase *, void *);
+static void common_precalc (struct cmd_t_test *);
+static void common_postcalc (struct cmd_t_test *);
+
+static int one_sample_calc (const struct ccase *, void *);
+static void one_sample_precalc (struct cmd_t_test *);
+static void one_sample_postcalc (struct cmd_t_test *);
+
+static int paired_calc (const struct ccase *, void *);
+static void paired_precalc (struct cmd_t_test *);
+static void paired_postcalc (struct cmd_t_test *);
+
+static void group_precalc (struct cmd_t_test *);
+static int group_calc (const struct ccase *, struct cmd_t_test *);
+static void group_postcalc (struct cmd_t_test *);
+
+
+static int compare_var_name (const void *a_, const void *b_, void *v_ UNUSED);
+static unsigned hash_var_name (const void *a_, void *v_ UNUSED);
+
+static void calculate(const struct casefile *cf, void *_mode);
+
+static int mode;
+
+static struct cmd_t_test cmd;
+
+static int bad_weight_warn;
+
int
cmd_t_test(void)
{
- int mode;
-
- struct ssbox stat_summary_box;
- struct trbox test_results_box;
- if (!lex_force_match_id ("T"))
- return CMD_FAILURE;
- lex_match ('-');
- lex_match_id ("TEST");
if ( !parse_t_test(&cmd) )
return CMD_FAILURE;
if (! cmd.sbc_criteria)
cmd.criteria=0.95;
- if ( cmd.sbc_testval + cmd.sbc_groups + cmd.sbc_pairs != 1 )
- {
- msg(SE,
- _("Exactly one of TESTVAL, GROUPS or PAIRS subcommands is required")
- );
- return CMD_FAILURE;
- }
+ {
+ int m=0;
+ if (cmd.sbc_testval) ++m;
+ if (cmd.sbc_groups) ++m;
+ if (cmd.sbc_pairs) ++m;
+
+ if ( m != 1)
+ {
+ msg(SE,
+ _("TESTVAL, GROUPS and PAIRS subcommands are mutually exclusive.")
+ );
+ return CMD_FAILURE;
+ }
+ }
if (cmd.sbc_testval)
mode=T_1_SAMPLE;
else
mode=T_PAIRED;
- if ( mode == T_PAIRED && cmd.sbc_variables)
+ if ( mode == T_PAIRED)
{
- msg(SE, _("VARIABLES subcommand is not appropriate with PAIRS"));
+ if (cmd.sbc_variables)
+ {
+ msg(SE, _("VARIABLES subcommand is not appropriate with PAIRS"));
+ return CMD_FAILURE;
+ }
+ else
+ {
+ /* Iterate through the pairs and put each variable that is a
+ member of a pair into cmd.v_variables */
+
+ int i;
+ struct hsh_iterator hi;
+ struct hsh_table *hash;
+ struct variable *v;
+
+ hash=hsh_create(n_pairs,compare_var_name,hash_var_name,0,0);
+
+ for (i=0; i < n_pairs; ++i)
+ {
+ hsh_insert(hash,pairs[i].v[0]);
+ hsh_insert(hash,pairs[i].v[1]);
+ }
+
+ assert(cmd.n_variables == 0);
+ cmd.n_variables = hsh_count(hash);
+
+ cmd.v_variables = xrealloc(cmd.v_variables,
+ sizeof(struct variable) * cmd.n_variables);
+ /* Iterate through the hash */
+ for (i=0,v = (struct variable *) hsh_first(hash,&hi);
+ v != 0;
+ v=hsh_next(hash,&hi) )
+ cmd.v_variables[i++]=v;
+
+ hsh_destroy(hash);
+ }
+ }
+ else if ( !cmd.sbc_variables)
+ {
+ msg(SE, _("One or more VARIABLES must be specified."));
return CMD_FAILURE;
}
- t_test_pool = pool_create ();
- ssbox_create(&stat_summary_box,&cmd,mode);
- trbox_create(&test_results_box,&cmd,mode);
+ /* If /MISSING=INCLUDE is set, then user missing values are ignored */
+ if (cmd.incl == TTS_INCLUDE )
+ value_is_missing = is_system_missing;
+ else
+ value_is_missing = is_missing;
- ssbox_populate(&stat_summary_box,&cmd);
- trbox_populate(&test_results_box,&cmd);
+ bad_weight_warn = 1;
- ssbox_finalize(&stat_summary_box);
- trbox_finalize(&test_results_box);
+ multipass_procedure_with_splits (calculate, &cmd);
- pool_destroy (t_test_pool);
+ n_pairs=0;
+ free(pairs);
+ pairs=0;
- t_test_pool=0;
+ if ( mode == T_IND_SAMPLES)
+ {
+ int i;
+ /* Destroy any group statistics we created */
+ for (i= 0 ; i < cmd.n_variables ; ++i )
+ {
+ free(cmd.v_variables[i]->p.t_t.gs);
+ }
+ }
return CMD_SUCCESS;
}
static int
-tts_custom_groups (struct cmd_t_test *cmd unused)
+tts_custom_groups (struct cmd_t_test *cmd UNUSED)
{
+
lex_match('=');
if (token != T_ALL &&
return 0;
}
- groups = parse_variable ();
- if (!groups)
+ indep_var = parse_variable ();
+ if (!indep_var)
{
lex_error ("expecting variable name in GROUPS subcommand");
return 0;
}
- if (groups->type == T_STRING && groups->width > MAX_SHORT_STRING)
+ if (indep_var->type == T_STRING && indep_var->width > MAX_SHORT_STRING)
{
msg (SE, _("Long string variable %s is not valid here."),
- groups->name);
+ indep_var->name);
return 0;
}
if (!lex_match ('('))
{
- if (groups->type == NUMERIC)
+ if (indep_var->type == NUMERIC)
{
- n_groups_values = 2;
groups_values[0].f = 1;
groups_values[1].f = 2;
+ criteria[0] = criteria[1] = CMP_EQ;
+ n_group_values = 2;
return 1;
}
else
}
}
- if (!parse_value (&groups_values[0],groups->type))
- return 0;
- n_groups_values = 1;
+ if (!parse_value (&groups_values[0],indep_var->type))
+ return 0;
lex_match (',');
if (lex_match (')'))
- return 1;
+ {
+ criteria[0] = CMP_LE;
+ criteria[1] = CMP_GT;
+ groups_values[1] = groups_values[0];
+ n_group_values = 1;
+ return 1;
+ }
- if (!parse_value (&groups_values[1],groups->type))
+ if (!parse_value (&groups_values[1],indep_var->type))
return 0;
- n_groups_values = 2;
-
+
+ n_group_values = 2;
if (!lex_force_match (')'))
return 0;
+ criteria[0] = criteria[1] = CMP_EQ;
return 1;
}
+
static int
-tts_custom_pairs (struct cmd_t_test *cmd unused)
+tts_custom_pairs (struct cmd_t_test *cmd UNUSED)
{
struct variable **vars;
int n_vars;
+ int n_pairs_local;
+
int n_before_WITH ;
int n_after_WITH = -1;
int paired ; /* Was the PAIRED keyword given ? */
n_before_WITH, n_after_WITH );
return 0;
}
- n_pairs=n_before_WITH;
+ n_pairs_local=n_before_WITH;
}
else if (n_before_WITH > 0) /* WITH keyword given, but not PAIRED keyword */
{
- n_pairs=n_before_WITH * n_after_WITH ;
+ n_pairs_local=n_before_WITH * n_after_WITH ;
}
else /* Neither WITH nor PAIRED keyword given */
{
}
/* how many ways can you pick 2 from n_vars ? */
- n_pairs = n_vars * (n_vars -1 ) /2 ;
+ n_pairs_local = n_vars * (n_vars -1 ) /2 ;
}
+
/* Allocate storage for the pairs */
- pairs = xrealloc(pairs,sizeof(pair_t) *n_pairs);
+ pairs = xrealloc(pairs, sizeof(struct pair) * (n_pairs + n_pairs_local) );
/* Populate the pairs with the appropriate variables */
if ( paired )
{
int i;
- assert(n_pairs == n_vars/2);
- for (i = 0; i < n_pairs ; ++i)
+ assert(n_pairs_local == n_vars/2);
+ for (i = 0; i < n_pairs_local ; ++i)
{
- pairs[i][0] = vars[i];
- pairs[i][1] = vars[i+n_pairs];
+ pairs[i].v[n_pairs+0] = vars[i];
+ pairs[i].v[n_pairs+1] = vars[i+n_pairs_local];
}
}
else if (n_before_WITH > 0) /* WITH keyword given, but not PAIRED keyword */
{
int i,j;
- int p=0;
+ int p=n_pairs;
for(i=0 ; i < n_before_WITH ; ++i )
{
for(j=0 ; j < n_after_WITH ; ++j)
{
- pairs[p][0] = vars[i];
- pairs[p][1] = vars[j+n_before_WITH];
+ pairs[p].v[0] = vars[i];
+ pairs[p].v[1] = vars[j+n_before_WITH];
++p;
}
}
else /* Neither WITH nor PAIRED given */
{
int i,j;
- int p=0;
+ int p=n_pairs;
for(i=0 ; i < n_vars ; ++i )
{
for(j=i+1 ; j < n_vars ; ++j)
{
- pairs[p][0] = vars[i];
- pairs[p][1] = vars[j];
+ pairs[p].v[0] = vars[i];
+ pairs[p].v[1] = vars[j];
++p;
}
}
}
+ n_pairs+=n_pairs_local;
+
return 1;
}
{
if (!lex_force_string ())
return 0;
- strncpy (v->s, ds_value (&tokstr), ds_length (&tokstr));
+ strncpy (v->s, ds_c_str (&tokstr), ds_length (&tokstr));
}
lex_get ();
ssbox_base_init(this, hsize,vsize);
tab_title (this->t, 0, _("Group Statistics"));
tab_vline(this->t,0,1,0,vsize);
- tab_text (this->t, 1, 0, TAB_CENTER | TAT_TITLE, groups->name);
+ tab_text (this->t, 1, 0, TAB_CENTER | TAT_TITLE, indep_var->name);
tab_text (this->t, 2, 0, TAB_CENTER | TAT_TITLE, _("N"));
tab_text (this->t, 3, 0, TAB_CENTER | TAT_TITLE, _("Mean"));
tab_text (this->t, 4, 0, TAB_CENTER | TAT_TITLE, _("Std. Deviation"));
{
int i;
+ char *val_lab0=0;
char *val_lab1=0;
- char *val_lab2=0;
- if ( groups->type == NUMERIC )
+ char prefix[2][3]={"",""};
+
+ if ( indep_var->type == NUMERIC )
{
- val_lab1 = val_labs_find( groups->val_labs,groups_values[0]);
- val_lab2 = val_labs_find( groups->val_labs,groups_values[1]);
+ val_lab0 = val_labs_find( indep_var->val_labs,groups_values[0]);
+ val_lab1 = val_labs_find( indep_var->val_labs,groups_values[1]);
}
else
{
- val_lab1 = groups_values[0].s;
- val_lab2 = groups_values[1].s;
+ val_lab0 = groups_values[0].s;
+ val_lab1 = groups_values[1].s;
+ }
+
+ if (n_group_values == 1)
+ {
+ strcpy(prefix[0],"< ");
+ strcpy(prefix[1],">=");
}
assert(ssb->t);
for (i=0; i < cmd->n_variables; ++i)
{
+ int g;
+
tab_text (ssb->t, 0, i*2+1, TAB_LEFT, cmd->v_variables[i]->name);
- if (val_lab1)
- tab_text (ssb->t, 1, i*2+1, TAB_LEFT, val_lab1);
+ if (val_lab0)
+ tab_text (ssb->t, 1, i*2+1, TAB_LEFT | TAT_PRINTF,
+ "%s%s", prefix[0], val_lab0);
else
- tab_float(ssb->t, 1 ,i*2+1, TAB_LEFT, groups_values[0].f, 2,0);
+ tab_text (ssb->t, 1, i*2+1, TAB_LEFT | TAT_PRINTF,
+ "%s%g", prefix[0], groups_values[0].f);
- if (val_lab2)
- tab_text (ssb->t, 1, i*2+1+1, TAB_LEFT, val_lab2);
+
+ if (val_lab1)
+ tab_text (ssb->t, 1, i*2+1+1, TAB_LEFT | TAT_PRINTF,
+ "%s%s", prefix[1], val_lab1);
else
- tab_float(ssb->t, 1 ,i*2+1+1, TAB_LEFT, groups_values[1].f,2,0);
+ tab_text (ssb->t, 1, i*2+1+1, TAB_LEFT | TAT_PRINTF,
+ "%s%g", prefix[1], groups_values[1].f);
+
+ /* Fill in the group statistics */
+ for ( g=0; g < 2 ; ++g )
+ {
+ struct group_statistics *gs = &cmd->v_variables[i]->p.t_t.gs[g];
+
+ tab_float(ssb->t, 2 ,i*2+g+1, TAB_RIGHT, gs->n, 2, 0);
+ tab_float(ssb->t, 3 ,i*2+g+1, TAB_RIGHT, gs->mean, 8, 2);
+ tab_float(ssb->t, 4 ,i*2+g+1, TAB_RIGHT, gs->std_dev, 8, 3);
+ tab_float(ssb->t, 5 ,i*2+g+1, TAB_RIGHT, gs->se_mean, 8, 3);
+ }
}
}
/* Initialize the paired values ssbox */
void
-ssbox_paired_init(struct ssbox *this, struct cmd_t_test *cmd unused)
+ssbox_paired_init(struct ssbox *this, struct cmd_t_test *cmd UNUSED)
{
int hsize=6;
/* Populate the ssbox for paired values */
void
-ssbox_paired_populate(struct ssbox *ssb,struct cmd_t_test *cmd unused)
+ssbox_paired_populate(struct ssbox *ssb,struct cmd_t_test *cmd UNUSED)
{
int i;
- struct string ds;
assert(ssb->t);
- ds_init(t_test_pool,&ds,15);
for (i=0; i < n_pairs; ++i)
{
- ds_clear(&ds);
+ int j;
- ds_printf(&ds,_("Pair %d"),i);
+ tab_text (ssb->t, 0, i*2+1, TAB_LEFT | TAT_PRINTF , _("Pair %d"),i);
- tab_text (ssb->t, 0, i*2+1, TAB_LEFT, ds.string);
- tab_text (ssb->t, 1, i*2+1, TAB_LEFT, pairs[i][0]->name);
- tab_text (ssb->t, 1, i*2+2, TAB_LEFT, pairs[i][1]->name);
- }
+ for (j=0 ; j < 2 ; ++j)
+ {
+ struct group_statistics *gs;
+
+ gs=&pairs[i].v[j]->p.t_t.ugs;
+
+ /* Titles */
+
+ tab_text (ssb->t, 1, i*2+j+1, TAB_LEFT, pairs[i].v[j]->name);
+
+ /* Values */
+ tab_float (ssb->t,2, i*2+j+1, TAB_RIGHT, pairs[i].mean[j], 8, 2);
+ tab_float (ssb->t,3, i*2+j+1, TAB_RIGHT, pairs[i].n, 2, 0);
+ tab_float (ssb->t,4, i*2+j+1, TAB_RIGHT, pairs[i].std_dev[j], 8, 3);
+ tab_float (ssb->t,5, i*2+j+1, TAB_RIGHT, pairs[i].std_dev[j]/sqrt(pairs[i].n), 8, 3);
- ds_destroy(&ds);
+ }
+ }
}
/* Populate the one sample ssbox */
for (i=0; i < cmd->n_variables; ++i)
{
+ struct group_statistics *gs;
+ gs= &cmd->v_variables[i]->p.t_t.ugs;
+
tab_text (ssb->t, 0, i+1, TAB_LEFT, cmd->v_variables[i]->name);
+ tab_float (ssb->t,1, i+1, TAB_RIGHT, gs->n, 2, 0);
+ tab_float (ssb->t,2, i+1, TAB_RIGHT, gs->mean, 8, 2);
+ tab_float (ssb->t,3, i+1, TAB_RIGHT, gs->std_dev, 8, 2);
+ tab_float (ssb->t,4, i+1, TAB_RIGHT, gs->se_mean, 8, 3);
}
}
/* Initialize the independent samples trbox */
void
trbox_independent_samples_init(struct trbox *self,
- struct cmd_t_test *cmd unused)
+ struct cmd_t_test *cmd UNUSED)
{
const int hsize=11;
const int vsize=cmd->n_variables*2+3;
- struct string ds;
-
assert(self);
self->populate = trbox_independent_samples_populate;
tab_hline(self->t,TAL_1, hsize-2,hsize-1,2);
tab_box(self->t,-1,-1,-1,TAL_1, hsize-2,2,hsize-1,vsize-1);
tab_joint_text(self->t, 2, 0, 3, 0,
- TAB_CENTER,_("Levine's Test for Equality of Variances"));
+ TAB_CENTER,_("Levene's Test for Equality of Variances"));
tab_joint_text(self->t, 4,0,hsize-1,0,
TAB_CENTER,_("t-test for Equality of Means"));
tab_text(self->t,9,2, TAB_CENTER | TAT_TITLE,_("Lower"));
tab_text(self->t,10,2, TAB_CENTER | TAT_TITLE,_("Upper"));
- ds_init(t_test_pool,&ds,80);
-
- ds_printf(&ds,_("%d%% Confidence Interval of the Difference"),
- (int)round(cmd->criteria*100.0));
-
- tab_joint_text(self->t,9,1,10,1,TAB_CENTER, ds.string);
+ tab_joint_text(self->t, 9, 1, 10, 1, TAB_CENTER | TAT_PRINTF,
+ _("%g%% Confidence Interval of the Difference"),
+ cmd->criteria*100.0);
- ds_destroy(&ds);
}
/* Populate the independent samples trbox */
assert(self);
for (i=0; i < cmd->n_variables; ++i)
{
+ double p,q;
+
+ double t;
+ double df;
+
+ double df1, df2;
+
+ double pooled_variance;
+ double std_err_diff;
+ double mean_diff;
+
+ struct group_statistics *gs0 = &cmd->v_variables[i]->p.t_t.gs[0];
+ struct group_statistics *gs1 = &cmd->v_variables[i]->p.t_t.gs[1];
+
tab_text (self->t, 0, i*2+3, TAB_LEFT, cmd->v_variables[i]->name);
tab_text (self->t, 1, i*2+3, TAB_LEFT, _("Equal variances assumed"));
+
+ tab_float(self->t, 2, i*2+3, TAB_CENTER,
+ cmd->v_variables[i]->p.t_t.levene, 8,3);
+
+ /* Now work out the significance of the Levene test */
+ df1 = 1; df2 = cmd->v_variables[i]->p.t_t.ugs.n - 2;
+ q = gsl_cdf_fdist_Q(cmd->v_variables[i]->p.t_t.levene, df1, df2);
+
+ tab_float(self->t, 3, i*2+3, TAB_CENTER, q, 8,3 );
+
+ df = gs0->n + gs1->n - 2.0 ;
+ tab_float (self->t, 5, i*2+3, TAB_RIGHT, df, 2, 0);
+
+ pooled_variance = ( (gs0->n )*pow2(gs0->s_std_dev)
+ +
+ (gs1->n )*pow2(gs1->s_std_dev)
+ ) / df ;
+
+ t = (gs0->mean - gs1->mean) / sqrt(pooled_variance) ;
+ t /= sqrt((gs0->n + gs1->n)/(gs0->n*gs1->n));
+
+ tab_float (self->t, 4, i*2+3, TAB_RIGHT, t, 8, 3);
+
+ p = gsl_cdf_tdist_P(t, df);
+ q = gsl_cdf_tdist_Q(t, df);
+
+ tab_float(self->t, 6, i*2+3, TAB_RIGHT, 2.0*(t>0?q:p) , 8, 3);
+
+ mean_diff = gs0->mean - gs1->mean;
+ tab_float(self->t, 7, i*2+3, TAB_RIGHT, mean_diff, 8, 3);
+
+
+ std_err_diff = sqrt( pow2(gs0->se_mean) + pow2(gs1->se_mean));
+ tab_float(self->t, 8, i*2+3, TAB_RIGHT, std_err_diff, 8, 3);
+
+
+ /* Now work out the confidence interval */
+ q = (1 - cmd->criteria)/2.0; /* 2-tailed test */
+
+ t = gsl_cdf_tdist_Qinv(q,df);
+ tab_float(self->t, 9, i*2+3, TAB_RIGHT,
+ mean_diff - t * std_err_diff, 8, 3);
+
+ tab_float(self->t, 10, i*2+3, TAB_RIGHT,
+ mean_diff + t * std_err_diff, 8, 3);
+
+
+ {
+ double se2;
+ /* Now for the \sigma_1 != \sigma_2 case */
tab_text (self->t, 1, i*2+3+1,
TAB_LEFT, _("Equal variances not assumed"));
+
+
+ se2 = (pow2(gs0->s_std_dev)/(gs0->n -1) ) +
+ (pow2(gs1->s_std_dev)/(gs1->n -1) );
+
+ t = mean_diff / sqrt(se2) ;
+ tab_float (self->t, 4, i*2+3+1, TAB_RIGHT, t, 8, 3);
+
+ df = pow2(se2) / (
+ (pow2(pow2(gs0->s_std_dev)/(gs0->n - 1 ))
+ /(gs0->n -1 )
+ )
+ +
+ (pow2(pow2(gs1->s_std_dev)/(gs1->n - 1 ))
+ /(gs1->n -1 )
+ )
+ ) ;
+ tab_float (self->t, 5, i*2+3+1, TAB_RIGHT, df, 8, 3);
+
+ p = gsl_cdf_tdist_P(t, df);
+ q = gsl_cdf_tdist_Q(t, df);
+
+ tab_float(self->t, 6, i*2+3+1, TAB_RIGHT, 2.0*(t>0?q:p) , 8, 3);
+
+ /* Now work out the confidence interval */
+ q = (1 - cmd->criteria)/2.0; /* 2-tailed test */
+
+ t = gsl_cdf_tdist_Qinv(q, df);
+
+ tab_float(self->t, 7, i*2+3+1, TAB_RIGHT, mean_diff, 8, 3);
+
+
+ tab_float(self->t, 8, i*2+3+1, TAB_RIGHT, std_err_diff, 8, 3);
+
+
+ tab_float(self->t, 9, i*2+3+1, TAB_RIGHT,
+ mean_diff - t * std_err_diff, 8, 3);
+
+ tab_float(self->t, 10, i*2+3+1, TAB_RIGHT,
+ mean_diff + t * std_err_diff, 8, 3);
+
+ }
}
}
/* Initialize the paired samples trbox */
void
trbox_paired_init(struct trbox *self,
- struct cmd_t_test *cmd unused)
+ struct cmd_t_test *cmd UNUSED)
{
const int hsize=10;
- const int vsize=n_pairs*2+3;
-
- struct string ds;
+ const int vsize=n_pairs+3;
self->populate = trbox_paired_populate;
- trbox_base_init(self,n_pairs*2,hsize);
+ trbox_base_init(self,n_pairs,hsize);
tab_title (self->t, 0, _("Paired Samples Test"));
tab_hline(self->t,TAL_1,2,6,1);
tab_vline(self->t,TAL_2,2,0,vsize);
tab_hline(self->t,TAL_1,5,6, 2);
tab_vline(self->t,TAL_0,6,0,1);
- ds_init(t_test_pool,&ds,80);
-
- ds_printf(&ds,_("%d%% Confidence Interval of the Difference"),
- (int)round(cmd->criteria*100.0));
-
- tab_joint_text(self->t,5,1,6,1,TAB_CENTER, ds.string);
-
- ds_destroy(&ds);
+ tab_joint_text(self->t, 5, 1, 6, 1, TAB_CENTER | TAT_PRINTF,
+ _("%g%% Confidence Interval of the Difference"),
+ cmd->criteria*100.0);
tab_text (self->t, 2, 2, TAB_CENTER | TAT_TITLE, _("Mean"));
tab_text (self->t, 3, 2, TAB_CENTER | TAT_TITLE, _("Std. Deviation"));
/* Populate the paired samples trbox */
void
trbox_paired_populate(struct trbox *trb,
- struct cmd_t_test *cmd unused)
+ struct cmd_t_test *cmd UNUSED)
{
int i;
- struct string ds;
-
- ds_init(t_test_pool,&ds,15);
for (i=0; i < n_pairs; ++i)
{
- ds_clear(&ds);
- ds_printf(&ds,_("Pair %d"),i);
+ double p,q;
+ double se_mean;
+
+ double n = pairs[i].n;
+ double t;
+ double df = n - 1;
+
+ tab_text (trb->t, 0, i+3, TAB_LEFT | TAT_PRINTF, _("Pair %d"),i);
+
+ tab_text (trb->t, 1, i+3, TAB_LEFT | TAT_PRINTF, "%s - %s",
+ pairs[i].v[0]->name, pairs[i].v[1]->name);
+
+ tab_float(trb->t, 2, i+3, TAB_RIGHT, pairs[i].mean_diff, 8, 4);
+
+ tab_float(trb->t, 3, i+3, TAB_RIGHT, pairs[i].std_dev_diff, 8, 5);
+
+ /* SE Mean */
+ se_mean = pairs[i].std_dev_diff / sqrt(n) ;
+ tab_float(trb->t, 4, i+3, TAB_RIGHT, se_mean, 8,5 );
+
+ /* Now work out the confidence interval */
+ q = (1 - cmd->criteria)/2.0; /* 2-tailed test */
+
+ t = gsl_cdf_tdist_Qinv(q, df);
+
+ tab_float(trb->t, 5, i+3, TAB_RIGHT,
+ pairs[i].mean_diff - t * se_mean , 8, 4);
+
+ tab_float(trb->t, 6, i+3, TAB_RIGHT,
+ pairs[i].mean_diff + t * se_mean , 8, 4);
+
+ t = (pairs[i].mean[0] - pairs[i].mean[1])
+ / sqrt (
+ ( pow2 (pairs[i].s_std_dev[0]) + pow2 (pairs[i].s_std_dev[1]) -
+ 2 * pairs[i].correlation *
+ pairs[i].s_std_dev[0] * pairs[i].s_std_dev[1] )
+ / (n - 1)
+ );
+
+ tab_float(trb->t, 7, i+3, TAB_RIGHT, t , 8,3 );
+
+ /* Degrees of freedom */
+ tab_float(trb->t, 8, i+3, TAB_RIGHT, df , 2, 0 );
+
+ p = gsl_cdf_tdist_P(t,df);
+ q = gsl_cdf_tdist_P(t,df);
+
+ tab_float(trb->t, 9, i+3, TAB_RIGHT, 2.0*(t>0?q:p) , 8, 3);
- tab_text (trb->t, 0, i*2+3, TAB_LEFT, ds.string);
- tab_text (trb->t, 1, i*2+3, TAB_LEFT, pairs[i][0]->name);
- tab_text (trb->t, 1, i*2+4, TAB_LEFT, pairs[i][1]->name);
}
- ds_destroy(&ds);
}
/* Initialize the one sample trbox */
const int hsize=7;
const int vsize=cmd->n_variables+3;
- struct string ds;
-
self->populate = trbox_one_sample_populate;
trbox_base_init(self, cmd->n_variables,hsize);
tab_title (self->t, 0, _("One-Sample Test"));
tab_hline(self->t, TAL_1, 1, hsize - 1, 1);
tab_vline(self->t, TAL_2, 1, 0, vsize);
- ds_init(t_test_pool, &ds, 80);
- ds_printf(&ds,_("Test Value = %f"),cmd->n_testval);
- tab_joint_text(self->t, 1, 0, hsize-1,0, TAB_CENTER,ds.string);
+
+ tab_joint_text(self->t, 1, 0, hsize-1,0, TAB_CENTER | TAT_PRINTF,
+ _("Test Value = %f"),cmd->n_testval);
+
tab_box(self->t, -1, -1, -1, TAL_1, 1,1,hsize-1,vsize-1);
- ds_clear(&ds);
- ds_printf(&ds,_("%d%% Confidence Interval of the Difference"),
- (int)round(cmd->criteria*100.0));
- tab_joint_text(self->t,5,1,6,1,TAB_CENTER, ds.string);
- ds_destroy(&ds);
+
+ tab_joint_text(self->t,5,1,6,1,TAB_CENTER | TAT_PRINTF,
+ _("%g%% Confidence Interval of the Difference"),
+ cmd->criteria*100.0);
+
tab_vline(self->t,TAL_0,6,1,1);
tab_hline(self->t,TAL_1,5,6,2);
tab_text (self->t, 1, 2, TAB_CENTER | TAT_TITLE, _("t"));
tab_text (self->t, 4, 2, TAB_CENTER | TAT_TITLE, _("Mean Difference"));
tab_text (self->t, 5, 2, TAB_CENTER | TAT_TITLE, _("Lower"));
tab_text (self->t, 6, 2, TAB_CENTER | TAT_TITLE, _("Upper"));
+
}
for (i=0; i < cmd->n_variables; ++i)
{
+ double t;
+ double p,q;
+ double df;
+ struct group_statistics *gs;
+ gs= &cmd->v_variables[i]->p.t_t.ugs;
+
+
tab_text (trb->t, 0, i+3, TAB_LEFT, cmd->v_variables[i]->name);
+
+ t = (gs->mean - cmd->n_testval ) * sqrt(gs->n) / gs->std_dev ;
+
+ tab_float (trb->t, 1, i+3, TAB_RIGHT, t, 8,3);
+
+ /* degrees of freedom */
+ df = gs->n - 1;
+
+ tab_float (trb->t, 2, i+3, TAB_RIGHT, df, 8,0);
+
+ p = gsl_cdf_tdist_P(t, df);
+ q = gsl_cdf_tdist_Q(t, df);
+
+ /* Multiply by 2 to get 2-tailed significance, makeing sure we've got
+ the correct tail*/
+ tab_float (trb->t, 3, i+3, TAB_RIGHT, 2.0*(t>0?q:p), 8,3);
+
+ tab_float (trb->t, 4, i+3, TAB_RIGHT, gs->mean_diff, 8,3);
+
+
+ q = (1 - cmd->criteria)/2.0; /* 2-tailed test */
+ t = gsl_cdf_tdist_Qinv(q, df);
+
+ tab_float (trb->t, 5, i+3, TAB_RIGHT,
+ gs->mean_diff - t * gs->se_mean, 8,4);
+
+ tab_float (trb->t, 6, i+3, TAB_RIGHT,
+ gs->mean_diff + t * gs->se_mean, 8,4);
}
}
{
tab_submit(trb->t);
}
+
+
+/* Create , populate and submit the Paired Samples Correlation box */
+void
+pscbox(void)
+{
+ const int rows=1+n_pairs;
+ const int cols=5;
+ int i;
+
+ struct tab_table *table;
+
+ table = tab_create (cols,rows,0);
+
+ tab_columns (table, SOM_COL_DOWN, 1);
+ tab_headers (table,0,0,1,0);
+ tab_box (table, TAL_2, TAL_2, TAL_0, TAL_1, 0, 0, cols -1, rows -1 );
+ tab_hline(table, TAL_2, 0, cols - 1, 1);
+ tab_vline(table, TAL_2, 2, 0, rows - 1);
+ tab_dim(table, tab_natural_dimensions);
+ tab_title(table, 0, _("Paired Samples Correlations"));
+
+ /* column headings */
+ tab_text(table, 2,0, TAB_CENTER | TAT_TITLE, _("N"));
+ tab_text(table, 3,0, TAB_CENTER | TAT_TITLE, _("Correlation"));
+ tab_text(table, 4,0, TAB_CENTER | TAT_TITLE, _("Sig."));
+
+ for (i=0; i < n_pairs; ++i)
+ {
+ double p,q;
+
+ double df = pairs[i].n -2;
+
+ double correlation_t =
+ pairs[i].correlation * sqrt(df) /
+ sqrt(1 - pow2(pairs[i].correlation));
+
+
+ /* row headings */
+ tab_text(table, 0,i+1, TAB_LEFT | TAT_TITLE | TAT_PRINTF,
+ _("Pair %d"), i);
+
+ tab_text(table, 1,i+1, TAB_LEFT | TAT_TITLE | TAT_PRINTF,
+ _("%s & %s"), pairs[i].v[0]->name, pairs[i].v[1]->name);
+
+
+ /* row data */
+ tab_float(table, 2, i+1, TAB_RIGHT, pairs[i].n, 4, 0);
+ tab_float(table, 3, i+1, TAB_RIGHT, pairs[i].correlation, 8, 3);
+
+ p = gsl_cdf_tdist_P(correlation_t, df);
+ q = gsl_cdf_tdist_Q(correlation_t, df);
+
+ tab_float(table, 4, i+1, TAB_RIGHT, 2.0*(correlation_t>0?q:p), 8, 3);
+ }
+
+ tab_submit(table);
+}
+
+
+
+/* Calculation Implementation */
+
+/* Per case calculations common to all variants of the T test */
+static int
+common_calc (const struct ccase *c, void *_cmd)
+{
+ int i;
+ struct cmd_t_test *cmd = (struct cmd_t_test *)_cmd;
+
+ double weight = dict_get_case_weight(default_dict,c,&bad_weight_warn);
+
+
+ /* Skip the entire case if /MISSING=LISTWISE is set */
+ if ( cmd->miss == TTS_LISTWISE )
+ {
+ for(i=0; i< cmd->n_variables ; ++i)
+ {
+ struct variable *v = cmd->v_variables[i];
+ const union value *val = &c->data[v->fv];
+
+ if (value_is_missing(val,v) )
+ {
+ return 0;
+ }
+ }
+ }
+
+ /* Listwise has to be implicit if the independent variable is missing ?? */
+ if ( cmd->sbc_groups )
+ {
+ const union value *gv = &c->data[indep_var->fv];
+ if ( value_is_missing(gv,indep_var) )
+ {
+ return 0;
+ }
+ }
+
+
+ for(i=0; i< cmd->n_variables ; ++i)
+ {
+ struct group_statistics *gs;
+ struct variable *v = cmd->v_variables[i];
+ const union value *val = &c->data[v->fv];
+
+ gs= &cmd->v_variables[i]->p.t_t.ugs;
+
+ if (! value_is_missing(val,v) )
+ {
+ gs->n+=weight;
+ gs->sum+=weight * val->f;
+ gs->ssq+=weight * val->f * val->f;
+ }
+ }
+ return 0;
+}
+
+/* Pre calculations common to all variants of the T test */
+static void
+common_precalc ( struct cmd_t_test *cmd )
+{
+ int i=0;
+
+ for(i=0; i< cmd->n_variables ; ++i)
+ {
+ struct group_statistics *gs;
+ gs= &cmd->v_variables[i]->p.t_t.ugs;
+
+ gs->sum=0;
+ gs->n=0;
+ gs->ssq=0;
+ gs->sum_diff=0;
+ }
+}
+
+/* Post calculations common to all variants of the T test */
+void
+common_postcalc ( struct cmd_t_test *cmd )
+{
+ int i=0;
+
+
+ for(i=0; i< cmd->n_variables ; ++i)
+ {
+ struct group_statistics *gs;
+ gs= &cmd->v_variables[i]->p.t_t.ugs;
+
+ 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;
+ }
+}
+
+/* Per case calculations for one sample t test */
+static int
+one_sample_calc (const struct ccase *c, void *cmd_)
+{
+ int i;
+ struct cmd_t_test *cmd = (struct cmd_t_test *)cmd_;
+
+
+ double weight = dict_get_case_weight(default_dict,c,&bad_weight_warn);
+
+ /* Skip the entire case if /MISSING=LISTWISE is set */
+ if ( cmd->miss == TTS_LISTWISE )
+ {
+ for(i=0; i< cmd->n_variables ; ++i)
+ {
+ struct variable *v = cmd->v_variables[i];
+ const union value *val = &c->data[v->fv];
+
+ if (value_is_missing(val,v) )
+ {
+ return 0;
+ }
+ }
+ }
+
+ for(i=0; i< cmd->n_variables ; ++i)
+ {
+ struct group_statistics *gs;
+ struct variable *v = cmd->v_variables[i];
+ const union value *val = &c->data[v->fv];
+
+ gs= &cmd->v_variables[i]->p.t_t.ugs;
+
+ if ( ! value_is_missing(val,v))
+ gs->sum_diff += weight * (val->f - cmd->n_testval);
+ }
+
+ return 0;
+}
+
+/* Pre calculations for one sample t test */
+static void
+one_sample_precalc ( struct cmd_t_test *cmd )
+{
+ int i=0;
+
+ for(i=0; i< cmd->n_variables ; ++i)
+ {
+ struct group_statistics *gs;
+ gs= &cmd->v_variables[i]->p.t_t.ugs;
+
+ gs->sum_diff=0;
+ }
+}
+
+/* Post calculations for one sample t test */
+static void
+one_sample_postcalc (struct cmd_t_test *cmd)
+{
+ int i=0;
+
+ for(i=0; i< cmd->n_variables ; ++i)
+ {
+ struct group_statistics *gs;
+ gs= &cmd->v_variables[i]->p.t_t.ugs;
+
+ gs->mean_diff = gs->sum_diff / gs->n ;
+ }
+}
+
+
+
+static int
+compare_var_name (const void *a_, const void *b_, void *v_ UNUSED)
+{
+ const struct variable *a = a_;
+ const struct variable *b = b_;
+
+ return strcmp(a->name,b->name);
+}
+
+static unsigned
+hash_var_name (const void *a_, void *v_ UNUSED)
+{
+ const struct variable *a = a_;
+
+ return hsh_hash_bytes (a->name, strlen(a->name));
+}
+
+
+
+static void
+paired_precalc (struct cmd_t_test *cmd UNUSED)
+{
+ int i;
+
+ for(i=0; i < n_pairs ; ++i )
+ {
+ pairs[i].n = 0;
+ pairs[i].sum[0] = 0; pairs[i].sum[1] = 0;
+ pairs[i].ssq[0] = 0; pairs[i].ssq[1] = 0;
+ pairs[i].sum_of_prod = 0;
+ pairs[i].correlation = 0;
+ pairs[i].sum_of_diffs = 0;
+ pairs[i].ssq_diffs = 0;
+ }
+
+}
+
+
+static int
+paired_calc (const struct ccase *c, void *cmd_)
+{
+ int i;
+
+ struct cmd_t_test *cmd = (struct cmd_t_test *) cmd_;
+
+ double weight = dict_get_case_weight(default_dict,c,&bad_weight_warn);
+
+ /* Skip the entire case if /MISSING=LISTWISE is set ,
+ AND one member of a pair is missing */
+ if ( cmd->miss == TTS_LISTWISE )
+ {
+ for(i=0; i < n_pairs ; ++i )
+ {
+ struct variable *v0 = pairs[i].v[0];
+ struct variable *v1 = pairs[i].v[1];
+
+ const union value *val0 = &c->data[v0->fv];
+ const union value *val1 = &c->data[v1->fv];
+
+ if ( value_is_missing(val0,v0) ||
+ value_is_missing(val1,v1) )
+ {
+ return 0;
+ }
+ }
+ }
+
+ for(i=0; i < n_pairs ; ++i )
+ {
+ struct variable *v0 = pairs[i].v[0];
+ struct variable *v1 = pairs[i].v[1];
+
+ const union value *val0 = &c->data[v0->fv];
+ const union value *val1 = &c->data[v1->fv];
+
+ if ( ( !value_is_missing(val0,v0) && !value_is_missing(val1,v1) ) )
+ {
+ pairs[i].n += weight;
+ pairs[i].sum[0] += weight * val0->f;
+ pairs[i].sum[1] += weight * val1->f;
+
+ pairs[i].ssq[0] += weight * pow2(val0->f);
+ pairs[i].ssq[1] += weight * pow2(val1->f);
+
+ pairs[i].sum_of_prod += weight * val0->f * val1->f ;
+
+ pairs[i].sum_of_diffs += weight * ( val0->f - val1->f ) ;
+ pairs[i].ssq_diffs += weight * pow2(val0->f - val1->f);
+ }
+ }
+
+ return 0;
+}
+
+static void
+paired_postcalc (struct cmd_t_test *cmd UNUSED)
+{
+ int i;
+
+ for(i=0; i < n_pairs ; ++i )
+ {
+ int j;
+ const double n = pairs[i].n;
+
+ for (j=0; j < 2 ; ++j)
+ {
+ pairs[i].mean[j] = pairs[i].sum[j] / n ;
+ pairs[i].s_std_dev[j] = sqrt((pairs[i].ssq[j] / n -
+ pow2(pairs[i].mean[j]))
+ );
+
+ pairs[i].std_dev[j] = sqrt(n/(n-1)*(pairs[i].ssq[j] / n -
+ pow2(pairs[i].mean[j]))
+ );
+ }
+
+ pairs[i].correlation = pairs[i].sum_of_prod / pairs[i].n -
+ pairs[i].mean[0] * pairs[i].mean[1] ;
+ /* correlation now actually contains the covariance */
+
+ pairs[i].correlation /= pairs[i].std_dev[0] * pairs[i].std_dev[1];
+ pairs[i].correlation *= pairs[i].n / ( pairs[i].n - 1 );
+
+ pairs[i].mean_diff = pairs[i].sum_of_diffs / n ;
+
+ pairs[i].std_dev_diff = sqrt ( n / (n - 1) * (
+ ( pairs[i].ssq_diffs / n )
+ -
+ pow2(pairs[i].mean_diff )
+ ) );
+ }
+}
+
+/* Return the group # corresponding to the
+ independent variable with the value val
+*/
+static int
+get_group(const union value *val, struct variable *indep)
+{
+ int i;
+
+ for (i = 0; i < 2 ; ++i )
+ {
+ const int cmp = compare_values(val,&groups_values[i],indep->width) ;
+ switch ( criteria[i])
+ {
+ case CMP_EQ:
+ if ( 0 == cmp ) return i;
+ break;
+ case CMP_LT:
+ if ( 0 > cmp ) return i;
+ break;
+ case CMP_LE:
+ if ( cmp <= 0 ) return i;
+ break;
+ case CMP_GT:
+ if ( cmp > 0 ) return i;
+ break;
+ case CMP_GE:
+ if ( cmp >= 0 ) return i;
+ break;
+ default:
+ assert(0);
+ };
+ }
+
+ /* No groups matched */
+ return -1;
+}
+
+
+static void
+group_precalc (struct cmd_t_test *cmd )
+{
+ int i;
+ int j;
+
+ for(i=0; i< cmd->n_variables ; ++i)
+ {
+ struct t_test_proc *ttpr = &cmd->v_variables[i]->p.t_t;
+
+ /* There's always 2 groups for a T - TEST */
+ ttpr->n_groups = 2;
+ ttpr->gs = xmalloc(sizeof(struct group_statistics) * 2) ;
+
+ for (j=0 ; j < 2 ; ++j)
+ {
+ ttpr->gs[j].sum = 0;
+ ttpr->gs[j].n = 0;
+ ttpr->gs[j].ssq = 0;
+
+ if ( n_group_values == 2 )
+ ttpr->gs[j].id = groups_values[j];
+ else
+ ttpr->gs[j].id = groups_values[0];
+ ttpr->gs[j].criterion = criteria[j];
+ }
+ }
+
+}
+
+static int
+group_calc (const struct ccase *c, struct cmd_t_test *cmd)
+{
+ int i;
+ int g;
+
+ const union value *gv = &c->data[indep_var->fv];
+
+ const double weight = dict_get_case_weight(default_dict,c,&bad_weight_warn);
+
+ if ( value_is_missing(gv,indep_var) )
+ {
+ return 0;
+ }
+
+ if ( cmd->miss == TTS_LISTWISE )
+ {
+ for(i=0; i< cmd->n_variables ; ++i)
+ {
+ struct variable *v = cmd->v_variables[i];
+ const union value *val = &c->data[v->fv];
+
+ if (value_is_missing(val,v) )
+ {
+ return 0;
+ }
+ }
+ }
+
+
+ gv = &c->data[indep_var->fv];
+
+ g = get_group(gv,indep_var);
+
+
+ /* If the independent variable doesn't match either of the values
+ for this case then move on to the next case */
+ if (g == -1 )
+ return 0;
+
+ for(i=0; i< cmd->n_variables ; ++i)
+ {
+ struct variable *var = cmd->v_variables[i];
+
+ struct group_statistics *gs = &var->p.t_t.gs[g];
+
+ const union value *val=&c->data[var->fv];
+
+ if ( !value_is_missing(val,var) )
+ {
+ gs->n+=weight;
+ gs->sum+=weight * val->f;
+ gs->ssq+=weight * pow2(val->f);
+ }
+ }
+
+ return 0;
+}
+
+
+static void
+group_postcalc ( struct cmd_t_test *cmd )
+{
+ int i;
+ int j;
+
+ for(i=0; i< cmd->n_variables ; ++i)
+ {
+ for (j=0 ; j < 2 ; ++j)
+ {
+ struct group_statistics *gs;
+ gs=&cmd->v_variables[i]->p.t_t.gs[j];
+
+ 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);
+ }
+ }
+}
+
+
+
+static void
+calculate(const struct casefile *cf, void *cmd_)
+{
+ struct ssbox stat_summary_box;
+ struct trbox test_results_box;
+
+ struct casereader *r;
+ const struct ccase *c;
+
+ struct cmd_t_test *cmd = (struct cmd_t_test *) cmd_;
+
+ common_precalc(cmd);
+ for(r = casefile_get_reader (cf);
+ casereader_read (r, &c) ; )
+ {
+ common_calc(c,cmd);
+ }
+ casereader_destroy (r);
+ common_postcalc(cmd);
+
+ switch(mode)
+ {
+ case T_1_SAMPLE:
+ one_sample_precalc(cmd);
+ for(r = casefile_get_reader (cf);
+ casereader_read (r, &c) ; )
+ {
+ one_sample_calc(c,cmd);
+ }
+ casereader_destroy (r);
+ one_sample_postcalc(cmd);
+
+ break;
+ case T_PAIRED:
+ paired_precalc(cmd);
+ for(r = casefile_get_reader (cf);
+ casereader_read (r, &c) ; )
+ {
+ paired_calc(c,cmd);
+ }
+ casereader_destroy (r);
+ paired_postcalc(cmd);
+
+ break;
+ case T_IND_SAMPLES:
+
+ group_precalc(cmd);
+ for(r = casefile_get_reader (cf);
+ casereader_read (r, &c) ; )
+ {
+ group_calc(c,cmd);
+ }
+ casereader_destroy (r);
+ group_postcalc(cmd);
+
+
+ levene(cf, indep_var, cmd->n_variables, cmd->v_variables,
+ (cmd->miss == TTS_LISTWISE)?LEV_LISTWISE:LEV_ANALYSIS ,
+ value_is_missing);
+ break;
+ }
+
+ ssbox_create(&stat_summary_box,cmd,mode);
+ ssbox_populate(&stat_summary_box,cmd);
+ ssbox_finalize(&stat_summary_box);
+
+ if ( mode == T_PAIRED)
+ pscbox();
+
+ trbox_create(&test_results_box,cmd,mode);
+ trbox_populate(&test_results_box,cmd);
+ trbox_finalize(&test_results_box);
+
+}
projects / pspp-builds.git / blobdiff