/* (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
{
+#if 1
/* The variables comprising the pair */
struct variable *v[2];
+#endif
+
+ /* 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;
}
}
+ /* 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;
procedure(common_precalc,common_calc,common_postcalc, NULL);
break;
case T_IND_SAMPLES:
procedure(group_precalc,group_calc,group_postcalc, NULL);
- levene(indep_var, cmd.n_variables, cmd.v_variables);
+ levene(indep_var, cmd.n_variables, cmd.v_variables,
+ (cmd.miss == TTS_LISTWISE)?LEV_LISTWISE:LEV_ANALYSIS ,
+ value_is_missing);
break;
}
free(pairs);
pairs=0;
-
if ( mode == T_IND_SAMPLES)
{
int i;
}
-
-
static int
tts_custom_pairs (struct cmd_t_test *cmd UNUSED)
{
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 */
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;
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 (
+ ( sqr (pairs[i].s_std_dev[0]) + sqr (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 );
which=1;
cdft(&which, &p, &q, &t, &df, &status, &bound);
-
if ( 0 != status )
{
msg( SE, _("Error calculating T statistic (cdft returned %d)."),status);
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) /
/* 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);
}
-
tab_float(table, 4, i+1, TAB_RIGHT, 2.0*(correlation_t>0?q:p), 8, 3);
-
}
tab_submit(table);
double weight = dict_get_case_weight(default_dict,c);
+
+ /* 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];
+ 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 )
+ {
+ 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;
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;
double weight = dict_get_case_weight(default_dict,c);
+ /* 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];
+ 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;
gs= &cmd.v_variables[i]->p.t_t.ugs;
- if (val->f != SYSMIS)
+ if ( ! value_is_missing(val,v))
gs->sum_diff += weight * (val->f - cmd.n_testval);
}
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;
}
}
{
int i;
+ double weight = dict_get_case_weight(default_dict,c);
+
+ /* 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];
+
+ union value *val0 = &c->data[v0->fv];
+ 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];
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 );
+ 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 * sqr(val0->f);
+ pairs[i].ssq[1] += weight * sqr(val1->f);
- pairs[i].sum_of_diffs += val0->f - val1->f ;
- pairs[i].ssq_diffs += sqr(val0->f - val1->f);
+#if 0
+ pairs[i].correlation += weight *
+ ( val0->f - pairs[i].v[0]->p.t_t.ugs.mean )
+ *
+ ( val1->f - pairs[i].v[1]->p.t_t.ugs.mean );
+#endif
+ 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 * sqr(val0->f - val1->f);
+ }
}
return 0;
for(i=0; i < n_pairs ; ++i )
{
- const double n = pairs[i].v[0]->p.t_t.ugs.n ;
+ 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 -
+ sqr(pairs[i].mean[j]))
+ );
+
+ pairs[i].std_dev[j] = sqrt(n/(n-1)*(pairs[i].ssq[j] / n -
+ sqr(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 );
+
+#if 0
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].correlation /= n - 1;
+#endif
pairs[i].mean_diff = pairs[i].sum_of_diffs / n ;
double weight = dict_get_case_weight(default_dict,c);
+ 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];
+ 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);
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];
- union value *val=&c->data[cmd.v_variables[i]->fv];
+ struct group_statistics *gs = &var->p.t_t.gs[g];
- gs->n+=weight;
- gs->sum+=weight * val->f;
- gs->ssq+=weight * sqr(val->f);
+ union value *val=&c->data[var->fv];
+
+ if ( !value_is_missing(val,var) )
+ {
+ gs->n+=weight;
+ gs->sum+=weight * val->f;
+ gs->ssq+=weight * sqr(val->f);
+ }
}
return 0;
projects / pspp-builds.git / blobdiff