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 "hash.h"
-#include "stats.h"
#include "t-test.h"
+#include "casefile.h"
#include "levene.h"
/* (specification)
/* (declarations) */
/* (functions) */
-static struct cmd_t_test cmd;
+
+
+
+/* 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 *indep_var;
static enum comparison criteria[2];
+
/* PAIRS: Number of pairs to be compared ; each pair. */
static int n_pairs = 0 ;
struct pair
/* The variables comprising the pair */
struct variable *v[2];
+ /* The number of valid variable pairs */
+ double n;
+
+ /* 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;
};
-static int common_calc (struct ccase *, void *);
-static void common_precalc (void *);
-static void common_postcalc (void *);
+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 (struct ccase *, void *);
-static void one_sample_precalc (void *);
-static void one_sample_postcalc (void *);
+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 (struct ccase *, void *);
-static void paired_precalc (void *);
-static void paired_postcalc (void *);
+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 (void *);
-static int group_calc (struct ccase *, void *);
-static void group_postcalc (void *);
+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;
hsh_destroy(hash);
}
}
-
-
- procedure(common_precalc,common_calc,common_postcalc, NULL);
-
- switch(mode)
+ else if ( !cmd.sbc_variables)
{
- case T_1_SAMPLE:
- procedure(one_sample_precalc,one_sample_calc,one_sample_postcalc, NULL);
- break;
- case T_PAIRED:
- procedure(paired_precalc,paired_calc,paired_postcalc, NULL);
- break;
- case T_IND_SAMPLES:
- procedure(group_precalc,group_calc,group_postcalc, NULL);
- levene(indep_var, cmd.n_variables, cmd.v_variables);
- break;
+ msg(SE, _("One or more VARIABLES must be specified."));
+ return CMD_FAILURE;
}
- ssbox_create(&stat_summary_box,&cmd,mode);
- ssbox_populate(&stat_summary_box,&cmd);
- ssbox_finalize(&stat_summary_box);
- if ( mode == T_PAIRED)
- pscbox();
+ /* 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;
- trbox_create(&test_results_box,&cmd,mode);
- trbox_populate(&test_results_box,&cmd);
- trbox_finalize(&test_results_box);
+ bad_weight_warn = 1;
+
+ multipass_procedure_with_splits (calculate, &cmd);
n_pairs=0;
free(pairs);
pairs=0;
-
if ( mode == T_IND_SAMPLES)
{
int i;
}
-
-
static int
tts_custom_pairs (struct cmd_t_test *cmd UNUSED)
{
{
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 ();
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, gs->mean, 8, 2);
- tab_float (ssb->t,3, i*2+j+1, TAB_RIGHT, gs->n, 2, 0);
- tab_float (ssb->t,4, i*2+j+1, TAB_RIGHT, gs->std_dev, 8, 3);
- tab_float (ssb->t,5, i*2+j+1, TAB_RIGHT, gs->se_mean, 8, 3);
+ 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);
}
-
}
-
}
/* Populate the one sample ssbox */
tab_text(self->t,10,2, TAB_CENTER | TAT_TITLE,_("Upper"));
tab_joint_text(self->t, 9, 1, 10, 1, TAB_CENTER | TAT_PRINTF,
- _("%d%% Confidence Interval of the Difference"),
- (int)round(cmd->criteria*100.0));
+ _("%g%% Confidence Interval of the Difference"),
+ cmd->criteria*100.0);
}
assert(self);
for (i=0; i < cmd->n_variables; ++i)
{
- int which =1;
double p,q;
- int status;
- double bound;
double t;
double df;
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 */
-
- which=1; df1 = 1; df2 = cmd->v_variables[i]->p.t_t.ugs.n - 2;
- cdff(&which,&p,&q,&cmd->v_variables[i]->p.t_t.levene,
- &df1,&df2,&status,&bound);
-
- if ( 0 != status )
- {
- msg( SE, _("Error calculating F statistic (cdff returned %d)."),status);
- }
+ 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 )*sqr(gs0->s_std_dev)
+ pooled_variance = ( (gs0->n )*pow2(gs0->s_std_dev)
+
- (gs1->n )*sqr(gs1->s_std_dev)
+ (gs1->n )*pow2(gs1->s_std_dev)
) / df ;
t = (gs0->mean - gs1->mean) / sqrt(pooled_variance) ;
tab_float (self->t, 4, i*2+3, TAB_RIGHT, t, 8, 3);
-
- which=1; /* get p & q from t & df */
- cdft(&which, &p, &q, &t, &df, &status, &bound);
- if ( 0 != status )
- {
- msg( SE, _("Error calculating T statistic (cdft returned %d)."),status);
- }
+ 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);
tab_float(self->t, 7, i*2+3, TAB_RIGHT, mean_diff, 8, 3);
- std_err_diff = sqrt( sqr(gs0->se_mean) + sqr(gs1->se_mean));
+ 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 */
- p = 1 - q ;
- which=2; /* Calc T from p,q and df */
- cdft(&which, &p, &q, &t, &df, &status, &bound);
- if ( 0 != status )
- {
- msg( SE, _("Error calculating T statistic (cdft returned %d)."),status);
- }
+ 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_LEFT, _("Equal variances not assumed"));
- se2 = (sqr(gs0->s_std_dev)/(gs0->n -1) ) +
- (sqr(gs1->s_std_dev)/(gs1->n -1) );
+ 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 = sqr(se2) / (
- (sqr(sqr(gs0->s_std_dev)/(gs0->n - 1 ))
+ df = pow2(se2) / (
+ (pow2(pow2(gs0->s_std_dev)/(gs0->n - 1 ))
/(gs0->n -1 )
)
+
- (sqr(sqr(gs1->s_std_dev)/(gs1->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);
- which=1; /* get p & q from t & df */
- cdft(&which, &p, &q, &t, &df, &status, &bound);
- if ( 0 != status )
- {
- msg( SE, _("Error calculating T statistic (cdft returned %d)."),status);
- }
+ 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 */
- p = 1 - q ;
- which=2; /* Calc T from p,q and df */
- cdft(&which, &p, &q, &t, &df, &status, &bound);
- if ( 0 != status )
- {
- msg( SE, _("Error calculating T statistic (cdft returned %d)."),status);
- }
+ t = gsl_cdf_tdist_Qinv(q, df);
tab_float(self->t, 7, i*2+3+1, TAB_RIGHT, mean_diff, 8, 3);
tab_vline(self->t,TAL_0,6,0,1);
tab_joint_text(self->t, 5, 1, 6, 1, TAB_CENTER | TAT_PRINTF,
- _("%d%% Confidence Interval of the Difference"),
- (int)round(cmd->criteria*100.0));
+ _("%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"));
for (i=0; i < n_pairs; ++i)
{
- int which =1;
double p,q;
- int status;
- double bound;
double se_mean;
- struct variable *v0 = pairs[i].v[0];
- struct variable *v1 = pairs[i].v[1];
-
- struct group_statistics *gs0 = &v0->p.t_t.ugs;
- struct group_statistics *gs1 = &v1->p.t_t.ugs;
-
- double n = gs0->n;
+ double n = pairs[i].n;
double t;
double df = n - 1;
/* Now work out the confidence interval */
q = (1 - cmd->criteria)/2.0; /* 2-tailed test */
- p = 1 - q ;
- which=2; /* Calc T from p,q and df */
- cdft(&which, &p, &q, &t, &df, &status, &bound);
- if ( 0 != status )
- {
- msg( SE, _("Error calculating T statistic (cdft returned %d)."),status);
- }
+ 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 = ( gs0->mean - gs1->mean)
- / sqrt (
- ( sqr(gs0->s_std_dev) + sqr(gs1->s_std_dev) -
- 2 * pairs[i].correlation * gs0->s_std_dev * gs1->s_std_dev )
- / (n-1) )
- ;
+ 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 );
- which=1;
- cdft(&which, &p, &q, &t, &df, &status, &bound);
-
- if ( 0 != status )
- {
- msg( SE, _("Error calculating T statistic (cdft returned %d)."),status);
- }
-
+ 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_joint_text(self->t,5,1,6,1,TAB_CENTER | TAT_PRINTF,
- _("%d%% Confidence Interval of the Difference"),
- (int)round(cmd->criteria*100.0));
+ _("%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);
for (i=0; i < cmd->n_variables; ++i)
{
- int which =1;
double t;
double p,q;
double df;
- int status;
- double bound;
struct group_statistics *gs;
gs= &cmd->v_variables[i]->p.t_t.ugs;
tab_float (trb->t, 2, i+3, TAB_RIGHT, df, 8,0);
- cdft(&which, &p, &q, &t, &df, &status, &bound);
-
- if ( 0 != status )
- {
- msg( SE, _("Error calculating T statistic (cdft returned %d)."),status);
- }
-
+ 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*/
q = (1 - cmd->criteria)/2.0; /* 2-tailed test */
- p = 1 - q ;
- which=2; /* Calc T from p,q and df */
- cdft(&which, &p, &q, &t, &df, &status, &bound);
- if ( 0 != status )
- {
- msg( SE, _("Error calculating T statistic (cdft returned %d)."),status);
- }
+ 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);
for (i=0; i < n_pairs; ++i)
{
- int which =1;
double p,q;
- int status;
- double bound;
-
- double df = pairs[i].v[0]->p.t_t.ugs.n -2;
+ double df = pairs[i].n -2;
double correlation_t =
pairs[i].correlation * sqrt(df) /
- sqrt(1 - sqr(pairs[i].correlation));
+ sqrt(1 - pow2(pairs[i].correlation));
/* row headings */
/* 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);
- tab_float(table, 2, i+1, TAB_RIGHT, pairs[i].v[0]->p.t_t.ugs.n , 4, 0);
-
-
- cdft(&which, &p, &q, &correlation_t, &df, &status, &bound);
-
- if ( 0 != status )
- {
- msg( SE, _("Error calculating T statistic (cdft returned %d)."),status);
- }
+ 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);
/* Per case calculations common to all variants of the T test */
static int
-common_calc (struct ccase *c, void *aux UNUSED)
+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;
+ }
+ }
- double weight = dict_get_case_weight(default_dict,c);
- for(i=0; i< cmd.n_variables ; ++i)
+ for(i=0; i< cmd->n_variables ; ++i)
{
struct group_statistics *gs;
- struct variable *v = cmd.v_variables[i];
- union value *val = &c->data[v->fv];
+ struct variable *v = cmd->v_variables[i];
+ const union value *val = &c->data[v->fv];
- gs= &cmd.v_variables[i]->p.t_t.ugs;
+ gs= &cmd->v_variables[i]->p.t_t.ugs;
- if (val->f != SYSMIS)
+ if (! value_is_missing(val,v) )
{
gs->n+=weight;
gs->sum+=weight * val->f;
/* Pre calculations common to all variants of the T test */
static void
-common_precalc (void *aux UNUSED)
+common_precalc ( struct cmd_t_test *cmd )
{
int i=0;
- for(i=0; i< cmd.n_variables ; ++i)
+ for(i=0; i< cmd->n_variables ; ++i)
{
struct group_statistics *gs;
- gs= &cmd.v_variables[i]->p.t_t.ugs;
+ gs= &cmd->v_variables[i]->p.t_t.ugs;
gs->sum=0;
gs->n=0;
/* Post calculations common to all variants of the T test */
void
-common_postcalc (void *aux UNUSED)
+common_postcalc ( struct cmd_t_test *cmd )
{
int i=0;
- for(i=0; i< cmd.n_variables ; ++i)
+
+ for(i=0; i< cmd->n_variables ; ++i)
{
struct group_statistics *gs;
- gs= &cmd.v_variables[i]->p.t_t.ugs;
+ gs= &cmd->v_variables[i]->p.t_t.ugs;
gs->mean=gs->sum / gs->n;
gs->s_std_dev= sqrt(
/* Per case calculations for one sample t test */
static int
-one_sample_calc (struct ccase *c, void *aux UNUSED)
+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);
- for(i=0; i< cmd.n_variables ; ++i)
+ 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];
- union value *val = &c->data[v->fv];
+ struct variable *v = cmd->v_variables[i];
+ const union value *val = &c->data[v->fv];
- gs= &cmd.v_variables[i]->p.t_t.ugs;
+ gs= &cmd->v_variables[i]->p.t_t.ugs;
- if (val->f != SYSMIS)
- gs->sum_diff += weight * (val->f - cmd.n_testval);
+ 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 (void *aux UNUSED)
+one_sample_precalc ( struct cmd_t_test *cmd )
{
- int i=0;
-
- for(i=0; i< cmd.n_variables ; ++i)
+ 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= &cmd->v_variables[i]->p.t_t.ugs;
gs->sum_diff=0;
}
/* Post calculations for one sample t test */
static void
-one_sample_postcalc (void *aux UNUSED)
+one_sample_postcalc (struct cmd_t_test *cmd)
{
int i=0;
- for(i=0; i< cmd.n_variables ; ++i)
+ for(i=0; i< cmd->n_variables ; ++i)
{
struct group_statistics *gs;
- gs= &cmd.v_variables[i]->p.t_t.ugs;
+ gs= &cmd->v_variables[i]->p.t_t.ugs;
-
gs->mean_diff = gs->sum_diff / gs->n ;
}
}
static void
-paired_precalc (void *aux UNUSED)
+paired_precalc (struct cmd_t_test *cmd UNUSED)
{
int i;
for(i=0; i < n_pairs ; ++i )
{
- pairs[i].correlation=0;
- pairs[i].sum_of_diffs=0;
- pairs[i].ssq_diffs=0;
+ 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 (struct ccase *c, void *aux UNUSED)
+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];
- union value *val0 = &c->data[v0->fv];
- union value *val1 = &c->data[v1->fv];
+ const union value *val0 = &c->data[v0->fv];
+ const union value *val1 = &c->data[v1->fv];
- pairs[i].correlation += ( val0->f - pairs[i].v[0]->p.t_t.ugs.mean )
- *
- ( val1->f - pairs[i].v[1]->p.t_t.ugs.mean );
+ 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_diffs += val0->f - val1->f ;
- pairs[i].ssq_diffs += sqr(val0->f - 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 (void *aux UNUSED)
+paired_postcalc (struct cmd_t_test *cmd UNUSED)
{
int i;
for(i=0; i < n_pairs ; ++i )
{
- const double n = pairs[i].v[0]->p.t_t.ugs.n ;
-
- pairs[i].correlation /= pairs[i].v[0]->p.t_t.ugs.std_dev *
- pairs[i].v[1]->p.t_t.ugs.std_dev ;
- pairs[i].correlation /= pairs[i].v[0]->p.t_t.ugs.n -1;
-
+ 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 )
-
- sqr(pairs[i].mean_diff )
+ pow2(pairs[i].mean_diff )
) );
}
}
static void
-group_precalc (void *aux UNUSED)
+group_precalc (struct cmd_t_test *cmd )
{
int i;
int j;
- for(i=0; i< cmd.n_variables ; ++i)
+ for(i=0; i< cmd->n_variables ; ++i)
{
- struct t_test_proc *ttpr = &cmd.v_variables[i]->p.t_t;
+ 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;
}
static int
-group_calc (struct ccase *c, void *aux UNUSED)
+group_calc (const struct ccase *c, struct cmd_t_test *cmd)
{
int i;
int g;
- union value *gv = &c->data[indep_var->fv];
- double weight = dict_get_case_weight(default_dict,c);
+ 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)
+ for(i=0; i< cmd->n_variables ; ++i)
{
- struct group_statistics *gs = &cmd.v_variables[i]->p.t_t.gs[g];
+ struct variable *var = cmd->v_variables[i];
+
+ struct group_statistics *gs = &var->p.t_t.gs[g];
- union value *val=&c->data[cmd.v_variables[i]->fv];
+ const union value *val=&c->data[var->fv];
- gs->n+=weight;
- gs->sum+=weight * val->f;
- gs->ssq+=weight * sqr(val->f);
+ 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 (void *aux UNUSED)
+group_postcalc ( struct cmd_t_test *cmd )
{
int i;
int j;
- for(i=0; i< cmd.n_variables ; ++i)
+ 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=&cmd->v_variables[i]->p.t_t.gs[j];
gs->mean = gs->sum / 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