X-Git-Url: https://pintos-os.org/cgi-bin/gitweb.cgi?a=blobdiff_plain;f=src%2Flanguage%2Fstats%2Fglm.c;h=004ae97feef474389de5015fbc8de71edad4f75f;hb=9666b94fcb0fe0230371d85a951ed18d1a34d538;hp=1ded71e9f1c6b69db56b6278a4ce8118bb6c5049;hpb=b6493cbb201307a2a5d1ff840a8347d75548cb85;p=pspp

diff --git a/src/language/stats/glm.c b/src/language/stats/glm.c
index 1ded71e9f1..004ae97fee 100644
--- a/src/language/stats/glm.c
+++ b/src/language/stats/glm.c
@@ -43,65 +43,63 @@
 #include "math/covariance.h"
 #include "math/interaction.h"
 #include "math/moments.h"
-#include "output/tab.h"
+#include "output/pivot-table.h"
 
 #include "gettext.h"
+#define N_(msgid) msgid
 #define _(msgid) gettext (msgid)
 
 struct glm_spec
-{
-  size_t n_dep_vars;
-  const struct variable **dep_vars;
+  {
+    const struct variable **dep_vars;
+    size_t n_dep_vars;
 
-  size_t n_factor_vars;
-  const struct variable **factor_vars;
+    const struct variable **factor_vars;
+    size_t n_factor_vars;
 
-  size_t n_interactions;
-  struct interaction **interactions;
+    struct interaction **interactions;
+    size_t n_interactions;
 
-  enum mv_class exclude;
+    enum mv_class exclude;
 
-  /* The weight variable */
-  const struct variable *wv;
+    const struct variable *wv;    /* The weight variable */
 
-  const struct dictionary *dict;
+    const struct dictionary *dict;
 
-  int ss_type;
-  bool intercept;
+    int ss_type;
+    bool intercept;
 
-  double alpha;
+    double alpha;
 
-  bool dump_coding;
-};
+    bool dump_coding;
+  };
 
 struct glm_workspace
-{
-  double total_ssq;
-  struct moments *totals;
+  {
+    double total_ssq;
+    struct moments *totals;
 
-  struct categoricals *cats;
+    struct categoricals *cats;
 
-  /* 
-     Sums of squares due to different variables. Element 0 is the SSE
-     for the entire model. For i > 0, element i is the SS due to
-     variable i.
-   */
-  gsl_vector *ssq;
-};
+    /*
+      Sums of squares due to different variables. Element 0 is the SSE
+      for the entire model. For i > 0, element i is the SS due to
+      variable i.
+    */
+    gsl_vector *ssq;
+  };
 
 
 /* Default design: all possible interactions */
 static void
 design_full (struct glm_spec *glm)
 {
-  int sz;
-  int i = 0;
   glm->n_interactions = (1 << glm->n_factor_vars) - 1;
-
   glm->interactions = xcalloc (glm->n_interactions, sizeof *glm->interactions);
 
   /* All subsets, with exception of the empty set, of [0, glm->n_factor_vars) */
-  for (sz = 1; sz <= glm->n_factor_vars; ++sz)
+  size_t i = 0;
+  for (size_t sz = 1; sz <= glm->n_factor_vars; ++sz)
     {
       gsl_combination *c = gsl_combination_calloc (glm->n_factor_vars, sz);
 
@@ -109,7 +107,7 @@ design_full (struct glm_spec *glm)
 	{
 	  struct interaction *iact = interaction_create (NULL);
 	  int e;
-	  for (e = 0 ; e < gsl_combination_k (c); ++e)
+	  for (e = 0; e < gsl_combination_k (c); ++e)
 	    interaction_add_variable (iact, glm->factor_vars [gsl_combination_get (c, e)]);
 
 	  glm->interactions[i++] = iact;
@@ -132,30 +130,27 @@ static bool parse_design_spec (struct lexer *lexer, struct glm_spec *glm);
 int
 cmd_glm (struct lexer *lexer, struct dataset *ds)
 {
-  int i;
   struct const_var_set *factors = NULL;
-  struct glm_spec glm;
   bool design = false;
-  glm.dict = dataset_dict (ds);
-  glm.n_dep_vars = 0;
-  glm.n_factor_vars = 0;
-  glm.n_interactions = 0;
-  glm.interactions = NULL;
-  glm.dep_vars = NULL;
-  glm.factor_vars = NULL;
-  glm.exclude = MV_ANY;
-  glm.intercept = true;
-  glm.wv = dict_get_weight (glm.dict);
-  glm.alpha = 0.05;
-  glm.dump_coding = false;
-  glm.ss_type = 3;
+  struct dictionary *dict = dataset_dict (ds);
+  struct glm_spec glm = {
+    .dict = dict,
+    .exclude = MV_ANY,
+    .intercept = true,
+    .wv = dict_get_weight (dict),
+    .alpha = 0.05,
+    .ss_type = 3,
+  };
 
+  int dep_vars_start = lex_ofs (lexer);
   if (!parse_variables_const (lexer, glm.dict,
 			      &glm.dep_vars, &glm.n_dep_vars,
 			      PV_NO_DUPLICATE | PV_NUMERIC))
     goto error;
+  int dep_vars_end = lex_ofs (lexer) - 1;
 
-  lex_force_match (lexer, T_BY);
+  if (!lex_force_match (lexer, T_BY))
+    goto error;
 
   if (!parse_variables_const (lexer, glm.dict,
 			      &glm.factor_vars, &glm.n_factor_vars,
@@ -164,12 +159,12 @@ cmd_glm (struct lexer *lexer, struct dataset *ds)
 
   if (glm.n_dep_vars > 1)
     {
-      msg (ME, _("Multivariate analysis is not yet implemented"));
+      lex_ofs_error (lexer, dep_vars_start, dep_vars_end,
+                     _("Multivariate analysis is not yet implemented"));
       return CMD_FAILURE;
     }
 
-  factors =
-    const_var_set_create_from_array (glm.factor_vars, glm.n_factor_vars);
+  factors = const_var_set_create_from_array (glm.factor_vars, glm.n_factor_vars);
 
   while (lex_token (lexer) != T_ENDCMD)
     {
@@ -182,16 +177,12 @@ cmd_glm (struct lexer *lexer, struct dataset *ds)
 		 && lex_token (lexer) != T_SLASH)
 	    {
 	      if (lex_match_id (lexer, "INCLUDE"))
-		{
-		  glm.exclude = MV_SYSTEM;
-		}
+                glm.exclude = MV_SYSTEM;
 	      else if (lex_match_id (lexer, "EXCLUDE"))
-		{
-		  glm.exclude = MV_ANY;
-		}
+                glm.exclude = MV_ANY;
 	      else
 		{
-		  lex_error (lexer, NULL);
+		  lex_error_expecting (lexer, "INCLUDE", "EXCLUDE");
 		  goto error;
 		}
 	    }
@@ -203,16 +194,12 @@ cmd_glm (struct lexer *lexer, struct dataset *ds)
 		 && lex_token (lexer) != T_SLASH)
 	    {
 	      if (lex_match_id (lexer, "INCLUDE"))
-		{
-		  glm.intercept = true;
-		}
+                glm.intercept = true;
 	      else if (lex_match_id (lexer, "EXCLUDE"))
-		{
-		  glm.intercept = false;
-		}
+                glm.intercept = false;
 	      else
 		{
-		  lex_error (lexer, NULL);
+		  lex_error_expecting (lexer, "INCLUDE", "EXCLUDE");
 		  goto error;
 		}
 	    }
@@ -220,121 +207,74 @@ cmd_glm (struct lexer *lexer, struct dataset *ds)
       else if (lex_match_id (lexer, "CRITERIA"))
 	{
 	  lex_match (lexer, T_EQUALS);
-	  if (lex_match_id (lexer, "ALPHA"))
-	    {
-	      if (lex_force_match (lexer, T_LPAREN))
-		{
-		  if (! lex_force_num (lexer))
-		    {
-		      lex_error (lexer, NULL);
-		      goto error;
-		    }
-		  
-		  glm.alpha = lex_number (lexer);
-		  lex_get (lexer);
-		  if ( ! lex_force_match (lexer, T_RPAREN))
-		    {
-		      lex_error (lexer, NULL);
-		      goto error;
-		    }
-		}
-	    }
-	  else
-	    {
-	      lex_error (lexer, NULL);
-	      goto error;
-	    }
+	  if (!lex_force_match_phrase (lexer, "ALPHA(")
+              || !lex_force_num (lexer))
+            goto error;
+          glm.alpha = lex_number (lexer);
+          lex_get (lexer);
+          if (!lex_force_match (lexer, T_RPAREN))
+            goto error;
 	}
       else if (lex_match_id (lexer, "METHOD"))
 	{
 	  lex_match (lexer, T_EQUALS);
-	  if ( !lex_force_match_id (lexer, "SSTYPE"))
-	    {
-	      lex_error (lexer, NULL);
-	      goto error;
-	    }
-
-	  if ( ! lex_force_match (lexer, T_LPAREN))
-	    {
-	      lex_error (lexer, NULL);
-	      goto error;
-	    }
-
-	  if ( ! lex_force_int (lexer))
-	    {
-	      lex_error (lexer, NULL);
-	      goto error;
-	    }
+	  if (!lex_force_match_phrase (lexer, "SSTYPE(")
+              || !lex_force_int_range (lexer, "SSTYPE", 1, 3))
+            goto error;
 
 	  glm.ss_type = lex_integer (lexer);
-	  if (1 > glm.ss_type  && 3 < glm.ss_type )
-	    {
-	      msg (ME, _("Only types 1, 2 & 3 sums of squares are currently implemented"));
-	      goto error;
-	    }
-
 	  lex_get (lexer);
 
-	  if ( ! lex_force_match (lexer, T_RPAREN))
-	    {
-	      lex_error (lexer, NULL);
-	      goto error;
-	    }
+	  if (!lex_force_match (lexer, T_RPAREN))
+            goto error;
 	}
       else if (lex_match_id (lexer, "DESIGN"))
 	{
 	  lex_match (lexer, T_EQUALS);
 
-	  if (! parse_design_spec (lexer, &glm))
+	  if (!parse_design_spec (lexer, &glm))
 	    goto error;
 
 	  if (glm.n_interactions > 0)
 	    design = true;
 	}
       else if (lex_match_id (lexer, "SHOWCODES"))
-	/* Undocumented debug option */
 	{
-	  lex_match (lexer, T_EQUALS);
-
+          /* Undocumented debug option */
 	  glm.dump_coding = true;
 	}
       else
 	{
-	  lex_error (lexer, NULL);
+	  lex_error_expecting (lexer, "MISSING", "INTERCEPT", "CRITERIA",
+                               "METHOD", "DESIGN");
 	  goto error;
 	}
     }
 
-  if ( ! design )
-    {
-      design_full (&glm);
-    }
+  if (!design)
+    design_full (&glm);
 
-  {
-    struct casegrouper *grouper;
-    struct casereader *group;
-    bool ok;
-
-    grouper = casegrouper_create_splits (proc_open (ds), glm.dict);
-    while (casegrouper_get_next_group (grouper, &group))
-      run_glm (&glm, group, ds);
-    ok = casegrouper_destroy (grouper);
-    ok = proc_commit (ds) && ok;
-  }
+  struct casegrouper *grouper = casegrouper_create_splits (proc_open (ds), glm.dict);
+  struct casereader *group;
+  while (casegrouper_get_next_group (grouper, &group))
+    run_glm (&glm, group, ds);
+  bool ok = casegrouper_destroy (grouper);
+  ok = proc_commit (ds) && ok;
 
   const_var_set_destroy (factors);
   free (glm.factor_vars);
+  for (size_t i = 0; i < glm.n_interactions; ++i)
+    interaction_destroy (glm.interactions[i]);
+
   free (glm.interactions);
   free (glm.dep_vars);
 
-
   return CMD_SUCCESS;
 
 error:
-
   const_var_set_destroy (factors);
   free (glm.factor_vars);
-  for (i = 0 ; i < glm.n_interactions; ++i)
+  for (size_t i = 0; i < glm.n_interactions; ++i)
     interaction_destroy (glm.interactions[i]);
 
   free (glm.interactions);
@@ -346,7 +286,7 @@ error:
 static inline bool
 not_dropped (size_t j, const bool *ff)
 {
-  return ! ff[j];
+  return !ff[j];
 }
 
 static void
@@ -356,11 +296,11 @@ fill_submatrix (const gsl_matrix * cov, gsl_matrix * submatrix, bool *dropped_f)
   size_t j;
   size_t n = 0;
   size_t m = 0;
-  
+
   for (i = 0; i < cov->size1; i++)
     {
       if (not_dropped (i, dropped_f))
-	{	  
+	{
 	  m = 0;
 	  for (j = 0; j < cov->size2; j++)
 	    {
@@ -369,7 +309,7 @@ fill_submatrix (const gsl_matrix * cov, gsl_matrix * submatrix, bool *dropped_f)
 		  gsl_matrix_set (submatrix, n, m,
 				  gsl_matrix_get (cov, i, j));
 		  m++;
-		}	
+		}
 	    }
 	  n++;
 	}
@@ -377,18 +317,18 @@ fill_submatrix (const gsl_matrix * cov, gsl_matrix * submatrix, bool *dropped_f)
 }
 
 
-/* 
+/*
    Type 1 sums of squares.
    Populate SSQ with the Type 1 sums of squares according to COV
  */
 static void
 ssq_type1 (struct covariance *cov, gsl_vector *ssq, const struct glm_spec *cmd)
 {
-  gsl_matrix *cm = covariance_calculate_unnormalized (cov);
+  const gsl_matrix *cm = covariance_calculate_unnormalized (cov);
   size_t i;
   size_t k;
-  bool *model_dropped = xcalloc (covariance_dim (cov), sizeof (*model_dropped));
-  bool *submodel_dropped = xcalloc (covariance_dim (cov), sizeof (*submodel_dropped));
+  bool *model_dropped = XCALLOC (covariance_dim (cov), bool);
+  bool *submodel_dropped = XCALLOC (covariance_dim (cov), bool);
   const struct categoricals *cats = covariance_get_categoricals (cov);
 
   size_t n_dropped_model = 0;
@@ -406,7 +346,7 @@ ssq_type1 (struct covariance *cov, gsl_vector *ssq, const struct glm_spec *cmd)
     {
       gsl_matrix *model_cov = NULL;
       gsl_matrix *submodel_cov = NULL;
-      
+
       n_dropped_submodel = n_dropped_model;
       for (i = cmd->n_dep_vars; i < covariance_dim (cov); i++)
 	{
@@ -415,10 +355,10 @@ ssq_type1 (struct covariance *cov, gsl_vector *ssq, const struct glm_spec *cmd)
 
       for (i = cmd->n_dep_vars; i < covariance_dim (cov); i++)
 	{
-	  const struct interaction * x = 
+	  const struct interaction * x =
 	    categoricals_get_interaction_by_subscript (cats, i - cmd->n_dep_vars);
 
-	  if ( x == cmd->interactions [k])
+	  if (x == cmd->interactions [k])
 	    {
 	      model_dropped[i] = false;
 	      n_dropped_model--;
@@ -436,7 +376,7 @@ ssq_type1 (struct covariance *cov, gsl_vector *ssq, const struct glm_spec *cmd)
 
       gsl_vector_set (ssq, k + 1,
 		      gsl_matrix_get (submodel_cov, 0, 0) - gsl_matrix_get (model_cov, 0, 0)
-		      );
+		);
 
       gsl_matrix_free (model_cov);
       gsl_matrix_free (submodel_cov);
@@ -444,21 +384,20 @@ ssq_type1 (struct covariance *cov, gsl_vector *ssq, const struct glm_spec *cmd)
 
   free (model_dropped);
   free (submodel_dropped);
-  gsl_matrix_free (cm);
 }
 
-/* 
+/*
    Type 2 sums of squares.
    Populate SSQ with the Type 2 sums of squares according to COV
  */
 static void
 ssq_type2 (struct covariance *cov, gsl_vector *ssq, const struct glm_spec *cmd)
 {
-  gsl_matrix *cm = covariance_calculate_unnormalized (cov);
+  const gsl_matrix *cm = covariance_calculate_unnormalized (cov);
   size_t i;
   size_t k;
-  bool *model_dropped = xcalloc (covariance_dim (cov), sizeof (*model_dropped));
-  bool *submodel_dropped = xcalloc (covariance_dim (cov), sizeof (*submodel_dropped));
+  bool *model_dropped = XCALLOC (covariance_dim (cov), bool);
+  bool *submodel_dropped = XCALLOC (covariance_dim (cov), bool);
   const struct categoricals *cats = covariance_get_categoricals (cov);
 
   for (k = 0; k < cmd->n_interactions; k++)
@@ -469,7 +408,7 @@ ssq_type2 (struct covariance *cov, gsl_vector *ssq, const struct glm_spec *cmd)
       size_t n_dropped_submodel = 0;
       for (i = cmd->n_dep_vars; i < covariance_dim (cov); i++)
 	{
-	  const struct interaction * x = 
+	  const struct interaction * x =
 	    categoricals_get_interaction_by_subscript (cats, i - cmd->n_dep_vars);
 
 	  model_dropped[i] = false;
@@ -480,7 +419,7 @@ ssq_type2 (struct covariance *cov, gsl_vector *ssq, const struct glm_spec *cmd)
 	      n_dropped_submodel++;
               submodel_dropped[i] = true;
 
-	      if ( cmd->interactions [k]->n_vars < x->n_vars)
+	      if (cmd->interactions [k]->n_vars < x->n_vars)
 		{
 		  assert (n_dropped_model < covariance_dim (cov));
 		  n_dropped_model++;
@@ -500,7 +439,7 @@ ssq_type2 (struct covariance *cov, gsl_vector *ssq, const struct glm_spec *cmd)
 
       gsl_vector_set (ssq, k + 1,
 		      gsl_matrix_get (submodel_cov, 0, 0) - gsl_matrix_get (model_cov, 0, 0)
-		      );
+		);
 
       gsl_matrix_free (model_cov);
       gsl_matrix_free (submodel_cov);
@@ -508,21 +447,20 @@ ssq_type2 (struct covariance *cov, gsl_vector *ssq, const struct glm_spec *cmd)
 
   free (model_dropped);
   free (submodel_dropped);
-  gsl_matrix_free (cm);
 }
 
-/* 
+/*
    Type 3 sums of squares.
    Populate SSQ with the Type 2 sums of squares according to COV
  */
 static void
 ssq_type3 (struct covariance *cov, gsl_vector *ssq, const struct glm_spec *cmd)
 {
-  gsl_matrix *cm = covariance_calculate_unnormalized (cov);
+  const gsl_matrix *cm = covariance_calculate_unnormalized (cov);
   size_t i;
   size_t k;
-  bool *model_dropped = xcalloc (covariance_dim (cov), sizeof (*model_dropped));
-  bool *submodel_dropped = xcalloc (covariance_dim (cov), sizeof (*submodel_dropped));
+  bool *model_dropped = XCALLOC (covariance_dim (cov), bool);
+  bool *submodel_dropped = XCALLOC (covariance_dim (cov), bool);
   const struct categoricals *cats = covariance_get_categoricals (cov);
 
   double ss0;
@@ -540,12 +478,12 @@ ssq_type3 (struct covariance *cov, gsl_vector *ssq, const struct glm_spec *cmd)
 
       for (i = cmd->n_dep_vars; i < covariance_dim (cov); i++)
 	{
-	  const struct interaction * x = 
+	  const struct interaction * x =
 	    categoricals_get_interaction_by_subscript (cats, i - cmd->n_dep_vars);
 
 	  model_dropped[i] = false;
 
-	  if ( cmd->interactions [k] == x)
+	  if (cmd->interactions [k] == x)
 	    {
 	      assert (n_dropped_model < covariance_dim (cov));
 	      n_dropped_model++;
@@ -565,8 +503,6 @@ ssq_type3 (struct covariance *cov, gsl_vector *ssq, const struct glm_spec *cmd)
       gsl_matrix_free (model_cov);
     }
   free (model_dropped);
-
-  gsl_matrix_free (cm);
 }
 
 
@@ -587,11 +523,21 @@ run_glm (struct glm_spec *cmd, struct casereader *input,
   struct glm_workspace ws;
   struct covariance *cov;
 
+  input  = casereader_create_filter_missing (input,
+					     cmd->dep_vars, cmd->n_dep_vars,
+					     cmd->exclude,
+					     NULL,  NULL);
+
+  input  = casereader_create_filter_missing (input,
+					     cmd->factor_vars, cmd->n_factor_vars,
+					     cmd->exclude,
+					     NULL,  NULL);
+
   ws.cats = categoricals_create (cmd->interactions, cmd->n_interactions,
-				 cmd->wv, cmd->exclude, MV_ANY);
+				 cmd->wv, MV_ANY);
 
   cov = covariance_2pass_create (cmd->n_dep_vars, cmd->dep_vars,
-				 ws.cats, cmd->wv, cmd->exclude);
+				 ws.cats, cmd->wv, cmd->exclude, true);
 
 
   c = casereader_peek (input, 0);
@@ -613,8 +559,7 @@ run_glm (struct glm_spec *cmd, struct casereader *input,
       double weight = dict_get_case_weight (dict, c, &warn_bad_weight);
 
       for (v = 0; v < cmd->n_dep_vars; ++v)
-	moments_pass_one (ws.totals, case_data (c, cmd->dep_vars[v])->f,
-			  weight);
+	moments_pass_one (ws.totals, case_num (c, cmd->dep_vars[v]), weight);
 
       covariance_accumulate_pass1 (cov, c);
     }
@@ -631,8 +576,7 @@ run_glm (struct glm_spec *cmd, struct casereader *input,
       double weight = dict_get_case_weight (dict, c, &warn_bad_weight);
 
       for (v = 0; v < cmd->n_dep_vars; ++v)
-	moments_pass_two (ws.totals, case_data (c, cmd->dep_vars[v])->f,
-			  weight);
+	moments_pass_two (ws.totals, case_num (c, cmd->dep_vars[v]), weight);
 
       covariance_accumulate_pass2 (cov, c);
     }
@@ -641,20 +585,20 @@ run_glm (struct glm_spec *cmd, struct casereader *input,
 
   if (cmd->dump_coding)
     {
-      struct tab_table *t =
-	covariance_dump_enc_header (cov,
-				    1 + casereader_count_cases (input));
+      struct pivot_table *t = covariance_dump_enc_header (cov);
       for (reader = input;
 	   (c = casereader_read (reader)) != NULL; case_unref (c))
 	{
 	  covariance_dump_enc (cov, c, t);
 	}
-      casereader_destroy (reader);
-      tab_submit (t);
+
+      pivot_table_submit (t);
     }
 
   {
-    gsl_matrix *cm = covariance_calculate_unnormalized (cov);
+    const gsl_matrix *ucm = covariance_calculate_unnormalized (cov);
+    gsl_matrix *cm = gsl_matrix_alloc (ucm->size1, ucm->size2);
+    gsl_matrix_memcpy (cm, ucm);
 
     //    dump_matrix (cm);
 
@@ -683,7 +627,6 @@ run_glm (struct glm_spec *cmd, struct casereader *input,
 	break;
       }
     //    dump_matrix (cm);
-
     gsl_matrix_free (cm);
   }
 
@@ -698,169 +641,120 @@ run_glm (struct glm_spec *cmd, struct casereader *input,
   taint_destroy (taint);
 }
 
-static const char *roman[] = 
-  {
-    "", /* The Romans had no concept of zero */
-    "I",
-    "II",
-    "III",
-    "IV"
-  };
+static void
+put_glm_row (struct pivot_table *table, int row,
+             double a, double b, double c, double d, double e)
+{
+  double entries[] = { a, b, c, d, e };
+
+  for (size_t col = 0; col < sizeof entries / sizeof *entries; col++)
+    if (entries[col] != SYSMIS)
+      pivot_table_put2 (table, col, row,
+                        pivot_value_new_number (entries[col]));
+}
 
 static void
 output_glm (const struct glm_spec *cmd, const struct glm_workspace *ws)
 {
-  const struct fmt_spec *wfmt =
-    cmd->wv ? var_get_print_format (cmd->wv) : &F_8_0;
+  struct pivot_table *table = pivot_table_create (
+    N_("Tests of Between-Subjects Effects"));
+
+  pivot_dimension_create (table, PIVOT_AXIS_COLUMN, N_("Statistics"),
+                          (cmd->ss_type == 1 ? N_("Type I Sum Of Squares")
+                           : cmd->ss_type == 2 ? N_("Type II Sum Of Squares")
+                           : N_("Type III Sum Of Squares")), PIVOT_RC_OTHER,
+                          N_("df"), PIVOT_RC_COUNT,
+                          N_("Mean Square"), PIVOT_RC_OTHER,
+                          N_("F"), PIVOT_RC_OTHER,
+                          N_("Sig."), PIVOT_RC_SIGNIFICANCE);
+
+  struct pivot_dimension *source = pivot_dimension_create (
+    table, PIVOT_AXIS_ROW, N_("Source"),
+    cmd->intercept ? N_("Corrected Model") : N_("Model"));
 
-  double intercept_ssq;
-  double ssq_effects;
   double n_total, mean;
-  double df_corr = 1.0;
-  double mse = 0;
-
-  int f;
-  int r;
-  const int heading_columns = 1;
-  const int heading_rows = 1;
-  struct tab_table *t;
-
-  const int nc = 6;
-  int nr = heading_rows + 3 + cmd->n_interactions;
-  if (cmd->intercept)
-    nr += 2;
-
-  msg (MW, "GLM is experimental.  Do not rely on these results.");
-  t = tab_create (nc, nr);
-  tab_title (t, _("Tests of Between-Subjects Effects"));
-
-  tab_headers (t, heading_columns, 0, heading_rows, 0);
-
-  tab_box (t, TAL_2, TAL_2, -1, TAL_1, 0, 0, nc - 1, nr - 1);
-
-  tab_hline (t, TAL_2, 0, nc - 1, heading_rows);
-  tab_vline (t, TAL_2, heading_columns, 0, nr - 1);
-
-  tab_text (t, 0, 0, TAB_CENTER | TAT_TITLE, _("Source"));
-
-  /* TRANSLATORS: The parameter is a roman numeral */
-  tab_text_format (t, 1, 0, TAB_CENTER | TAT_TITLE,
-		   _("Type %s Sum of Squares"), 
-		   roman[cmd->ss_type]);
-  tab_text (t, 2, 0, TAB_CENTER | TAT_TITLE, _("df"));
-  tab_text (t, 3, 0, TAB_CENTER | TAT_TITLE, _("Mean Square"));
-  tab_text (t, 4, 0, TAB_CENTER | TAT_TITLE, _("F"));
-  tab_text (t, 5, 0, TAB_CENTER | TAT_TITLE, _("Sig."));
-
   moments_calculate (ws->totals, &n_total, &mean, NULL, NULL, NULL);
 
-  df_corr += categoricals_df_total (ws->cats);
-
-  r = heading_rows;
-  if (cmd->intercept)
-    tab_text (t, 0, r, TAB_LEFT | TAT_TITLE, _("Corrected Model"));
-  else
-    tab_text (t, 0, r, TAB_LEFT | TAT_TITLE, _("Model"));
-
-  r++;
-
-  mse = gsl_vector_get (ws->ssq, 0) / (n_total - df_corr);
-
-  intercept_ssq = pow2 (mean * n_total) / n_total;
+  double df_corr = 1.0 + categoricals_df_total (ws->cats);
 
-  ssq_effects = 0.0;
+  double mse = gsl_vector_get (ws->ssq, 0) / (n_total - df_corr);
+  double intercept_ssq = pow2 (mean * n_total) / n_total;
   if (cmd->intercept)
     {
-      const double df = 1.0;
-      const double F = intercept_ssq / df / mse;
-      tab_text (t, 0, r, TAB_LEFT | TAT_TITLE, _("Intercept"));
-      tab_double (t, 1, r, 0, intercept_ssq, NULL);
-      tab_double (t, 2, r, 0, 1.00, wfmt);
-      tab_double (t, 3, r, 0, intercept_ssq / df, NULL);
-      tab_double (t, 4, r, 0, F, NULL);
-      tab_double (t, 5, r, 0, gsl_cdf_fdist_Q (F, df, n_total - df_corr),
-		  NULL);
-      r++;
+      int row = pivot_category_create_leaf (
+        source->root, pivot_value_new_text (N_("Intercept")));
+
+      /* The intercept for unbalanced models is of limited use and
+	 nobody knows how to calculate it properly */
+      if (categoricals_isbalanced (ws->cats))
+        {
+          const double df = 1.0;
+          const double F = intercept_ssq / df / mse;
+          put_glm_row (table, row, intercept_ssq, 1.0, intercept_ssq / df,
+                       F, gsl_cdf_fdist_Q (F, df, n_total - df_corr));
+        }
     }
 
-  for (f = 0; f < cmd->n_interactions; ++f)
+  double ssq_effects = 0.0;
+  for (int f = 0; f < cmd->n_interactions; ++f)
     {
-      struct string str = DS_EMPTY_INITIALIZER;
       double df = categoricals_df (ws->cats, f);
-
       double ssq = gsl_vector_get (ws->ssq, f + 1);
-      double F;
-
       ssq_effects += ssq;
-
-      if (! cmd->intercept) 
+      if (!cmd->intercept)
 	{
 	  df++;
 	  ssq += intercept_ssq;
 	}
+      double F = ssq / df / mse;
 
-      F = ssq / df / mse;
+      struct string str = DS_EMPTY_INITIALIZER;
       interaction_to_string (cmd->interactions[f], &str);
-      tab_text (t, 0, r, TAB_LEFT | TAT_TITLE, ds_cstr (&str));
-      ds_destroy (&str);
-
-      tab_double (t, 1, r, 0, ssq, NULL);
-      tab_double (t, 2, r, 0, df, wfmt);
-      tab_double (t, 3, r, 0, ssq / df, NULL);
-      tab_double (t, 4, r, 0, F, NULL);
+      int row = pivot_category_create_leaf (
+        source->root, pivot_value_new_user_text_nocopy (ds_steal_cstr (&str)));
 
-      tab_double (t, 5, r, 0, gsl_cdf_fdist_Q (F, df, n_total - df_corr),
-		  NULL);
-      r++;
+      put_glm_row (table, row, ssq, df, ssq / df, F,
+                   gsl_cdf_fdist_Q (F, df, n_total - df_corr));
     }
 
   {
     /* Model / Corrected Model */
     double df = df_corr;
     double ssq = ws->total_ssq - gsl_vector_get (ws->ssq, 0);
-    double F;
-
-    if ( cmd->intercept )
-      df --;
+    if (cmd->intercept)
+      df--;
     else
       ssq += intercept_ssq;
-
-    F = ssq / df / mse;
-    tab_double (t, 1, heading_rows, 0, ssq, NULL);
-    tab_double (t, 2, heading_rows, 0, df, wfmt);
-    tab_double (t, 3, heading_rows, 0, ssq / df, NULL);
-    tab_double (t, 4, heading_rows, 0, F, NULL);
-
-    tab_double (t, 5, heading_rows, 0,
-		gsl_cdf_fdist_Q (F, df, n_total - df_corr), NULL);
+    double F = ssq / df / mse;
+    put_glm_row (table, 0, ssq, df, ssq / df, F,
+                 gsl_cdf_fdist_Q (F, df, n_total - df_corr));
   }
 
   {
+    int row = pivot_category_create_leaf (source->root,
+                                          pivot_value_new_text (N_("Error")));
     const double df = n_total - df_corr;
     const double ssq = gsl_vector_get (ws->ssq, 0);
     const double mse = ssq / df;
-    tab_text (t, 0, r, TAB_LEFT | TAT_TITLE, _("Error"));
-    tab_double (t, 1, r, 0, ssq, NULL);
-    tab_double (t, 2, r, 0, df, wfmt);
-    tab_double (t, 3, r++, 0, mse, NULL);
+    put_glm_row (table, row, ssq, df, mse, SYSMIS, SYSMIS);
   }
 
   {
-    tab_text (t, 0, r, TAB_LEFT | TAT_TITLE, _("Total"));
-    tab_double (t, 1, r, 0, ws->total_ssq + intercept_ssq, NULL);
-    tab_double (t, 2, r, 0, n_total, wfmt);
-    
-    r++;
+    int row = pivot_category_create_leaf (source->root,
+                                          pivot_value_new_text (N_("Total")));
+    put_glm_row (table, row, ws->total_ssq + intercept_ssq, n_total,
+                 SYSMIS, SYSMIS, SYSMIS);
   }
 
   if (cmd->intercept)
     {
-      tab_text (t, 0, r, TAB_LEFT | TAT_TITLE, _("Corrected Total"));
-      tab_double (t, 1, r, 0, ws->total_ssq, NULL);
-      tab_double (t, 2, r, 0, n_total - 1.0, wfmt);
+      int row = pivot_category_create_leaf (
+        source->root, pivot_value_new_text (N_("Corrected Total")));
+      put_glm_row (table, row, ws->total_ssq, n_total - 1.0, SYSMIS,
+                   SYSMIS, SYSMIS);
     }
 
-  tab_submit (t);
+  pivot_table_submit (table);
 }
 
 #if 0
@@ -887,20 +781,20 @@ static bool
 parse_nested_variable (struct lexer *lexer, struct glm_spec *glm)
 {
   const struct variable *v = NULL;
-  if ( ! lex_match_variable (lexer, glm->dict, &v))
+  if (!lex_match_variable (lexer, glm->dict, &v))
     return false;
 
   if (lex_match (lexer, T_LPAREN))
     {
-      if ( ! parse_nested_variable (lexer, glm))
+      if (!parse_nested_variable (lexer, glm))
 	return false;
 
-      if ( ! lex_force_match (lexer, T_RPAREN))
+      if (!lex_force_match (lexer, T_RPAREN))
 	return false;
     }
 
-  lex_error (lexer, "Nested variables are not yet implemented"); return false;  
-  return true;
+  lex_error (lexer, "Nested variables are not yet implemented");
+  return false;
 }
 
 /* A design term is an interaction OR a nested variable */
@@ -911,12 +805,12 @@ parse_design_term (struct lexer *lexer, struct glm_spec *glm)
   if (parse_design_interaction (lexer, glm->dict, &iact))
     {
       /* Interaction parsing successful.  Add to list of interactions */
-      glm->interactions = xrealloc (glm->interactions, sizeof *glm->interactions * ++glm->n_interactions);
+      glm->interactions = xrealloc (glm->interactions, sizeof (*glm->interactions) * ++glm->n_interactions);
       glm->interactions[glm->n_interactions - 1] = iact;
       return true;
     }
 
-  if ( parse_nested_variable (lexer, glm))
+  if (parse_nested_variable (lexer, glm))
     return true;
 
   return false;
@@ -934,11 +828,10 @@ parse_design_spec (struct lexer *lexer, struct glm_spec *glm)
   if  (lex_token (lexer) == T_ENDCMD || lex_token (lexer) == T_SLASH)
     return true;
 
-  if ( ! parse_design_term (lexer, glm))
+  if (!parse_design_term (lexer, glm))
     return false;
 
   lex_match (lexer, T_COMMA);
 
   return parse_design_spec (lexer, glm);
 }
-