nc - 1, nr - 1);
tab_vline (t, TAL_2, heading_columns, 0, nr - 1);
+
tab_vline (t, TAL_1, 1, heading_rows, nr - 1);
+ /* Row Headers */
for (r = 0 ; r < corr->n_vars1 ; ++r)
{
tab_text (t, 0, 1 + r * rows_per_variable, TAB_LEFT | TAT_TITLE,
tab_hline (t, TAL_1, 0, nc - 1, r * rows_per_variable + 1);
}
+ /* Column Headers */
for (c = 0 ; c < matrix_cols ; ++c)
{
- const struct variable *v = corr->n_vars_total > corr->n_vars1 ? corr->vars[corr->n_vars_total - corr->n_vars1 + c] : corr->vars[c];
+ const struct variable *v = corr->n_vars_total > corr->n_vars1 ?
+ corr->vars[corr->n_vars1 + c] : corr->vars[c];
tab_text (t, heading_columns + c, 0, TAB_LEFT | TAT_TITLE, var_to_string (v));
}
for (c = 0 ; c < matrix_cols ; ++c)
{
unsigned char flags = 0;
- const int col_index = corr->n_vars_total - corr->n_vars1 + c;
+ const int col_index = corr->n_vars_total > corr->n_vars1 ?
+ corr->n_vars1 + c :
+ c;
double pearson = gsl_matrix_get (cm, r, col_index);
double w = gsl_matrix_get (samples, r, col_index);
double sig = opts->tails * significance_of_correlation (pearson, w);
if ( opts->missing_type != CORR_LISTWISE )
tab_double (t, c + heading_columns, row + rows_per_variable - 1, 0, w, wfmt);
- if ( c != r)
+ if ( col_index != r)
tab_double (t, c + heading_columns, row + 1, 0, sig, NULL);
- if ( opts->sig && c != r && sig < 0.05)
+ if ( opts->sig && col_index != r && sig < 0.05)
flags = TAB_EMPH;
tab_double (t, c + heading_columns, row, flags, pearson, NULL);
if ( opts->statistics & STATS_DESCRIPTIVES)
output_descriptives (corr, mean_matrix, var_matrix, samples_matrix);
- output_correlation (corr, opts,
- corr_matrix,
- samples_matrix,
- cov_matrix);
+ output_correlation (corr, opts, corr_matrix,
+ samples_matrix, cov_matrix);
covariance_destroy (cov);
gsl_matrix_free (corr_matrix);