#include "var.h"
#include "vfm.h"
#include "pool.h"
+#include "hash.h"
+#include "stats.h"
+#include "t-test.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,
static struct cmd_t_test cmd;
-
static struct pool *t_test_pool ;
/* Variable for the GROUPS subcommand, if given. */
/* GROUPS: Number of values specified by the user; the values
specified if any. */
+
static int n_groups_values;
static union value groups_values[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 correlation coefficient between the variables */
+ double correlation;
+
+ /* The sum of the differences */
+ double sum_of_diffs;
+
+ /* 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) ;
/* 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 */
};
-static int common_calc (struct ccase *);
-static void common_precalc (void);
-static void common_postcalc (void);
+static int common_calc (struct ccase *, void *);
+static void common_precalc (void *);
+static void common_postcalc (void *);
+
+static int one_sample_calc (struct ccase *, void *);
+static void one_sample_precalc (void *);
+static void one_sample_postcalc (void *);
+
+static int paired_calc (struct ccase *, void *);
+static void paired_precalc (void *);
+static void paired_postcalc (void *);
+
+static void group_precalc (void *);
+static int group_calc (struct ccase *, void *);
+static void group_postcalc (void *);
+
+
+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 int one_sample_calc (struct ccase *);
-static void one_sample_precalc (void);
-static void one_sample_postcalc (void);
int
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"));
- return CMD_FAILURE;
+ 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);
+ }
}
- procedure(common_precalc,common_calc,common_postcalc);
- if (mode == T_1_SAMPLE)
- procedure(one_sample_precalc,one_sample_calc,one_sample_postcalc);
+ procedure(common_precalc,common_calc,common_postcalc, NULL);
+
+ switch(mode)
+ {
+ 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(groups, cmd.n_variables, cmd.v_variables);
+ break;
+ }
t_test_pool = pool_create ();
ssbox_create(&stat_summary_box,&cmd,mode);
- trbox_create(&test_results_box,&cmd,mode);
-
ssbox_populate(&stat_summary_box,&cmd);
- trbox_populate(&test_results_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);
pool_destroy (t_test_pool);
t_test_pool=0;
+
+
+ n_pairs=0;
+ free(pairs);
+ pairs=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('=');
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;
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;
}
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)
else
tab_float(ssb->t, 1 ,i*2+1, TAB_LEFT, groups_values[0].f, 2,0);
+
if (val_lab2)
tab_text (ssb->t, 1, i*2+1+1, TAB_LEFT, val_lab2);
else
tab_float(ssb->t, 1 ,i*2+1+1, TAB_LEFT, groups_values[1].f,2,0);
+
+ /* 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);
+
+ 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, 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_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);
}
- ds_destroy(&ds);
}
/* Populate the one sample ssbox */
for (i=0; i < cmd->n_variables; ++i)
{
- struct t_test_proc *ttp;
- ttp= &cmd->v_variables[i]->p.t_t;
+ 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, ttp->n, 2, 0);
- tab_float (ssb->t,2, i+1, TAB_RIGHT, ttp->mean, 8, 2);
- tab_float (ssb->t,3, i+1, TAB_RIGHT, ttp->std_dev, 8, 2);
- tab_float (ssb->t,4, i+1, TAB_RIGHT, ttp->se_mean, 8, 3);
+ 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,
+ _("%d%% Confidence Interval of the Difference"),
+ (int)round(cmd->criteria*100.0));
- ds_destroy(&ds);
}
/* Populate the independent samples trbox */
assert(self);
for (i=0; i < cmd->n_variables; ++i)
{
+ int which =1;
+ double p,q;
+ int status;
+ double bound;
+
+ 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 */
+
+ 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);
+ }
+
+ 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)
+ +
+ (gs1->n )*sqr(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);
+
+
+ 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);
+ }
+
+ 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( sqr(gs0->se_mean) + sqr(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);
+ }
+
+ 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 = (sqr(gs0->s_std_dev)/(gs0->n -1) ) +
+ (sqr(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 ))
+ /(gs0->n -1 )
+ )
+ +
+ (sqr(sqr(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);
+ }
+
+ 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);
+ }
+
+
+ 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,
+ _("%d%% Confidence Interval of the Difference"),
+ (int)round(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);
+ 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 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 */
+ 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);
+ }
+
+ 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) )
+ ;
+
+ 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);
+ }
+
+
+ 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,
+ _("%d%% Confidence Interval of the Difference"),
+ (int)round(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"));
double df;
int status;
double bound;
- struct t_test_proc *ttp;
- ttp= &cmd->v_variables[i]->p.t_t;
+ 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 = (ttp->mean - cmd->n_testval ) * sqrt(ttp->n) / ttp->std_dev ;
+ 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 = ttp->n - 1;
+ df = gs->n - 1;
tab_float (trb->t, 2, i+3, TAB_RIGHT, df, 8,0);
cdft(&which, &p, &q, &t, &df, &status, &bound);
- assert(status == 0 ); /* FIXME: use proper error message */
+ if ( 0 != status )
+ {
+ msg( SE, _("Error calculating T statistic (cdft returned %d)."),status);
+ }
+
- /* Multiply by 2 to get 2-tailed significance */
- tab_float (trb->t, 3, i+3, TAB_RIGHT, q*2.0, 8,3);
+ /* 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, ttp->mean_diff, 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 */
p = 1 - q ;
which=2; /* Calc T from p,q and df */
cdft(&which, &p, &q, &t, &df, &status, &bound);
- assert(status == 0 ); /* FIXME: proper error message */
+ if ( 0 != status )
+ {
+ msg( SE, _("Error calculating T statistic (cdft returned %d)."),status);
+ }
tab_float (trb->t, 5, i+3, TAB_RIGHT,
- ttp->mean_diff - t * ttp->se_mean, 8,4);
+ gs->mean_diff - t * gs->se_mean, 8,4);
tab_float (trb->t, 6, i+3, TAB_RIGHT,
- ttp->mean_diff + t * ttp->se_mean, 8,4);
+ gs->mean_diff + t * gs->se_mean, 8,4);
}
}
}
+/* 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)
+ {
+ int which =1;
+ double p,q;
+
+ int status;
+ double bound;
+
+ double df = pairs[i].v[0]->p.t_t.ugs.n -2;
+
+ double correlation_t =
+ pairs[i].correlation * sqrt(df) /
+ sqrt(1 - sqr(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, 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);
+ }
+
+
+ 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 (struct ccase *c)
+common_calc (struct ccase *c, void *aux UNUSED)
{
int i;
for(i=0; i< cmd.n_variables ; ++i)
{
- struct t_test_proc *ttp;
+ struct group_statistics *gs;
struct variable *v = cmd.v_variables[i];
union value *val = &c->data[v->fv];
- ttp= &cmd.v_variables[i]->p.t_t;
+ gs= &cmd.v_variables[i]->p.t_t.ugs;
if (val->f != SYSMIS)
{
- ttp->n+=weight;
- ttp->sum+=weight * val->f;
- ttp->ssq+=weight * val->f * val->f;
+ 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 (void)
+common_precalc (void *aux UNUSED)
{
int i=0;
-
+
for(i=0; i< cmd.n_variables ; ++i)
{
- struct t_test_proc *ttp;
- ttp= &cmd.v_variables[i]->p.t_t;
+ struct group_statistics *gs;
+ gs= &cmd.v_variables[i]->p.t_t.ugs;
- ttp->sum=0;
- ttp->n=0;
- ttp->ssq=0;
- ttp->sum_diff=0;
+ 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 (void)
+common_postcalc (void *aux UNUSED)
{
int i=0;
for(i=0; i< cmd.n_variables ; ++i)
{
- struct t_test_proc *ttp;
- ttp= &cmd.v_variables[i]->p.t_t;
+ struct group_statistics *gs;
+ gs= &cmd.v_variables[i]->p.t_t.ugs;
- ttp->mean=ttp->sum / ttp->n;
- ttp->std_dev= sqrt(
- ttp->n/(ttp->n-1) *
- ( (ttp->ssq / ttp->n ) - ttp->mean * ttp->mean )
+ gs->mean=gs->sum / gs->n;
+ gs->s_std_dev= sqrt(
+ ( (gs->ssq / gs->n ) - gs->mean * gs->mean )
) ;
- ttp->se_mean = ttp->std_dev / sqrt(ttp->n);
+ gs->std_dev= sqrt(
+ gs->n/(gs->n-1) *
+ ( (gs->ssq / gs->n ) - gs->mean * gs->mean )
+ ) ;
- ttp->mean_diff= ttp->sum_diff / ttp->n;
+ 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 (struct ccase *c)
+one_sample_calc (struct ccase *c, void *aux UNUSED)
{
int i;
for(i=0; i< cmd.n_variables ; ++i)
{
- struct t_test_proc *ttp;
+ struct group_statistics *gs;
struct variable *v = cmd.v_variables[i];
union value *val = &c->data[v->fv];
- ttp= &cmd.v_variables[i]->p.t_t;
+ gs= &cmd.v_variables[i]->p.t_t.ugs;
if (val->f != SYSMIS)
- ttp->sum_diff += weight * (val->f - cmd.n_testval);
+ gs->sum_diff += weight * (val->f - cmd.n_testval);
}
return 0;
/* Pre calculations for one sample t test */
static void
-one_sample_precalc (void)
+one_sample_precalc (void *aux UNUSED)
{
int i=0;
for(i=0; i< cmd.n_variables ; ++i)
{
- struct t_test_proc *ttp;
- ttp= &cmd.v_variables[i]->p.t_t;
+ struct group_statistics *gs;
+ gs= &cmd.v_variables[i]->p.t_t.ugs;
- ttp->sum_diff=0;
+ gs->sum_diff=0;
}
}
/* Post calculations for one sample t test */
static void
-one_sample_postcalc (void)
+one_sample_postcalc (void *aux UNUSED)
{
int i=0;
for(i=0; i< cmd.n_variables ; ++i)
{
- struct t_test_proc *ttp;
- ttp= &cmd.v_variables[i]->p.t_t;
+ 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 (void *aux 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;
+ }
+
+}
+
+
+static int
+paired_calc (struct ccase *c, void *aux UNUSED)
+{
+ int i;
+
+ 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];
+
+ 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 );
+
+ pairs[i].sum_of_diffs += val0->f - val1->f ;
+ pairs[i].ssq_diffs += sqr(val0->f - val1->f);
+
+ }
+
+ return 0;
+}
+
+static void
+paired_postcalc (void *aux UNUSED)
+{
+ int i;
+ for(i=0; i < n_pairs ; ++i )
+ {
+ const double n = pairs[i].v[0]->p.t_t.ugs.n ;
- ttp->mean_diff = ttp->sum_diff / ttp->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;
+
+
+ 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 )
+ ) );
}
}
+
+static int
+get_group(const union value *val, struct variable *var)
+{
+ if ( 0 == compare_values(val,&groups_values[0],var->width) )
+ return 0;
+ else if (0 == compare_values(val,&groups_values[1],var->width) )
+ return 1;
+
+ /* Never reached */
+ assert(0);
+ return -1;
+}
+
+
+static void
+group_precalc (void *aux UNUSED)
+{
+ 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;
+ ttpr->gs[j].id = groups_values[j];
+ }
+ }
+
+}
+
+static int
+group_calc (struct ccase *c, void *aux UNUSED)
+{
+ int i;
+ union value *gv = &c->data[groups->fv];
+
+ double weight = dict_get_case_weight(default_dict,c);
+
+ gv = &c->data[groups->fv];
+
+ for(i=0; i< cmd.n_variables ; ++i)
+ {
+ int g = get_group(gv,groups);
+
+ struct group_statistics *gs = &cmd.v_variables[i]->p.t_t.gs[g];
+
+ union value *val=&c->data[cmd.v_variables[i]->fv];
+
+ gs->n+=weight;
+ gs->sum+=weight * val->f;
+ gs->ssq+=weight * sqr(val->f);
+ }
+
+ return 0;
+}
+
+
+static void
+group_postcalc (void *aux UNUSED)
+{
+ 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);
+ }
+ }
+}
+