# Test of nonparametric ANOVA for dependent categorical measures - Friedman's test

use strict;
use warnings;
use Test::More tests => 14;
use constant EPS => 1e-2;

BEGIN { use_ok('Statistics::ANOVA') };

my $aov = Statistics::ANOVA->new();
isa_ok($aov, 'Statistics::ANOVA');

# Example from Siegal (1956) p. 167ff.

my @c1 = (9,6,9);
my @c2 = (4,5,1);
my @c3 = (1,2,2);
my @c4 = (7,8,6);

my %ref_vals = (
    df_b => 3,
	chi_value => 7.400,
	p_value => 2*0.033,
	mrank_1 => 3.67,
	mrank_2 => 1.67,
	mrank_3 => 1.33,
	mrank_4 => 3.33,
);

eval {$aov->load_data({ 1 => \@c1, 2 => \@c2, 3 => \@c3, 4 => \@c4 });};
ok(!$@, $@);

eval {$aov->anova(independent => 0, parametric => 0, ordinal =>0, f_equiv => 0);};
ok(!$@, $@);

ok( about_equal($aov->{'_stat'}->{'df_b'}, $ref_vals{'df_b'}), "Dependent Nonparametric Categorical:df_b: $aov->{'_stat'}->{'df_b'} = $ref_vals{'df_b'}" );

ok( about_equal($aov->{'_stat'}->{'chi_value'}, $ref_vals{'chi_value'}), "Dependent Nonparametric Categorical:chi_value: $aov->{'_stat'}->{'chi_value'} = $ref_vals{'chi_value'}" );

ok( about_equal($aov->{'_stat'}->{'p_value'}, $ref_vals{'p_value'}), "Dependent Nonparametric Categorical:p_value: $aov->{'_stat'}->{'p_value'} = $ref_vals{'p_value'}" );

# Example from Hollander & Wolfe (1999), p. 274ff:

my @p1 = (5.40, 5.85, 5.20, 5.55, 5.90, 5.45, 5.40, 5.45, 5.25, 5.85, 5.25, 5.65, 5.60, 5.05, 5.50, 5.45, 5.55, 5.45, 5.50, 5.65, 5.70, 6.30);
my @p2 = (5.50, 5.70, 5.60, 5.50, 5.85, 5.55, 5.40, 5.50, 5.15, 5.80, 5.20, 5.55, 5.35, 5.00, 5.50, 5.55, 5.55, 5.50, 5.45, 5.60, 5.65, 6.30);
my @p3 = (5.55, 5.75, 5.50, 5.40, 5.70, 5.60, 5.35, 5.35, 5.00, 5.70, 5.10, 5.45, 5.45, 4.95, 5.40, 5.50, 5.35, 5.55, 5.25, 5.40, 5.55, 6.25);

%ref_vals = (
	df_b => 2,
	chi_value_uncorr => 10.64,
	chi_value => 11.14,
	p_value => .004,
);

eval {$aov->load_data({ 1 => \@p1, 2 => \@p2, 3 => \@p3});};
ok(!$@, $@);

eval {$aov->anova(independent => 0, parametric => 0, ordinal =>0, f_equiv => 0);};
ok(!$@, $@);

ok( about_equal($aov->{'_stat'}->{'df_b'}, $ref_vals{'df_b'}), "Dependent Nonparametric Categorical:df_b: $aov->{'_stat'}->{'df_b'} = $ref_vals{'df_b'}" );

ok( about_equal($aov->{'_stat'}->{'chi_value'}, $ref_vals{'chi_value'}), "Dependent Nonparametric Categorical:chi_value: $aov->{'_stat'}->{'chi_value'} = $ref_vals{'chi_value'}" );

ok( about_equal($aov->{'_stat'}->{'p_value'}, $ref_vals{'p_value'}), "Dependent Nonparametric Categorical:p_value: $aov->{'_stat'}->{'p_value'} = $ref_vals{'p_value'}" );

eval {$aov->anova(independent => 0, parametric => 0, ordinal =>0, f_equiv => 0, correct_ties => 0);};
ok(!$@, $@);

ok( about_equal($aov->{'_stat'}->{'chi_value'}, $ref_vals{'chi_value_uncorr'}), "Dependent Nonparametric Categorical:chi_value: $aov->{'_stat'}->{'chi_value'} = $ref_vals{'chi_value_uncorr'}" );

sub about_equal {
    return 1 if $_[0] + EPS > $_[1] and $_[0] - EPS < $_[1];
    return 0;
}