The following Matlab project contains the source code and Matlab examples used for tukey's test of additivity for a two-way classification analysis of variance. . Tukey's test of additivity for a two-way analysis of variance design with replication (can be equal or unequal sample sizes) or without replication.

The following Matlab project contains the source code and Matlab examples used for single-factor analysis of variance test. . Computes the single-factor Analysis of Variance Model I or Model II for equal or unequal sample sizes.

The following Matlab project contains the source code and Matlab examples used for kruskal-wallis' nonparametric analysis of variance. . Kruskal-Wallis' nonparametric analysis of variance test the difference among groups and it is applicable for equal or unequal sample sizes and if there are tied ranks. This file uses both the chi-squared and F approximations.

The following Matlab project contains the source code and Matlab examples used for single-factor analysis of variance test using only means and variances. . Computes a single-factor analysis of variances test using only means and variances(without data).

The following Matlab project contains the source code and Matlab examples used for bartlett's test for homogeneity of variances. . Bartlett's test is developed to estimate whether more than two groups are homoscedastic. Bartlett's statistic is approximated by the chi-square distribution. The file needs the data matrix and the significance level.

The following Matlab project contains the source code and Matlab examples used for o'brien's test for homogeneity of variances. . In the Obrien's test to check out the homogeneity of variances the data are transforming to yij = ((nj-1.5)*nj*((xij-mean(xj))**2)-((0.5)*(var(xj))*(nj-1)))/((nj-1)*(nj-2)) and uses the F distribution performing an one-way ANOVA using y as the dependent variable.

The following Matlab project contains the source code and Matlab examples used for levene's test for homogeneity of variances. . Levene's F test is used to test the null hypothesis that multiple population variances corresponding to multiplesamples are equal.

The following Matlab project contains the source code and Matlab examples used for welch's test for homogeneity of variances. . Welch's test is developed to estimate whether more than two groups are homoscedastic. Also the Welch's test can be used as an alternative analysis of variance when samples variances are unequal.

The following Matlab project contains the source code and Matlab examples used for calulation of the a priori statistical power of a one-way manova test. . This file estimates the a priori statistical power of a single-factor Multivariate Analysis of Variance (MANOVA).

The following Matlab project contains the source code and Matlab examples used for computing of a standard (simple) split-plot design analysis of variance. . This file computes the standard (simple) split-plot design analysis of variance, taking into account the linear model: x_jkl = µ + a_j + ß_k + d_jk + Þ_l + (ßÞ)_kl + e_jkl where j = 1,.

The following Matlab project contains the source code and Matlab examples used for computes a balanced incomplete block design [bibd] analysis of variance. . This file computes a balanced incomplete block design [BIBD] analysis of variance.

The following Matlab project contains the source code and Matlab examples used for computes a multivariate analysis of variance for equal or unequal sample sizes. . Computes a Multivariate Analysis of Variance for equal or unequal sample sizes.

The following Matlab project contains the source code and Matlab examples used for computes a two-way multivariate analysis of variance for equal or unequal sample sizes. . Computing of a two-way multivariate analysis of variance for equal or unequal sample sizes by the testing of the mean differences in several variables among several samples with two factors.

The following Matlab project contains the source code and Matlab examples used for conover's two sample squared ranks test for equality of variance. Performs the nonparametric squared ranks test on quality of variance for two samples.

The following Matlab project contains the source code and Matlab examples used for repeated measures two-way analysis of variance test. . ANOVA with two within-subject variables is used to analyze the relationship between two independent variables and the dependent variable.

The following Matlab project contains the source code and Matlab examples used for repeated measures mixed two-way analysis of variance test. . ANOVA with between- and within- subject variables (mixed) is used to analyze the relationship for designs that have a combination of between and within-subject variables.

The following Matlab project contains the source code and Matlab examples used for anova and variance components for genetic data. These files are an adaptation of the ANOVA variance component estimators to be used in the analysis of genetic data, specifically Cockerham's 1969 Theta.

The following Matlab project contains the source code and Matlab examples used for statistical power of a performed (a posteriori) single-factor manova. . Estimating of the statistical power of a performed (a posteriori) single factor Multivariate Analysis of Variance (MANOVA).

The following Matlab project contains the source code and Matlab examples used for identification of outliers in a one-way analysis of variance model ii (random effects). . In a one-way analysis of variance random effects model one would expect that the measurements lie close together because the same quantity was measured and states that the class effects stem from a common source and therefore should not difer too much.

The following Matlab project contains the source code and Matlab examples used for planned (a priori) analysis of variance test. . Computes a planned (a priori) Analysis of Variance test.

The following Matlab project contains the source code and Matlab examples used for 2^3 factorial design analysis. . This m-file is used in experiments involving several factors where it is necessary to investigate the joint effects (main and interactions) of the factors on a response variable and determine by a formal analysis of variance which factor effects are nonzero.

The following Matlab project contains the source code and Matlab examples used for 2^2 factorial design analysis. . This m-file is used in experiments involving several factors where it is necessary to investigate the joint effects (main and interactions) of the factors on a response variable and determine by a formal analysis of variance which factor effects are nonzero.

The following Matlab project contains the source code and Matlab examples used for three-way analysis of variance with repeated measures on two factors test. . This is a three-factor analysis of variance design in which there are repeated measures on two of the factors.

The following Matlab project contains the source code and Matlab examples used for adjustment of the f statistic by epsilon on repeated measures anova. . Sphericity is an assumption of repeated measure ANOVA.

The following Matlab project contains the source code and Matlab examples used for profile analysis of multivariate repeated measures. . Profile analysis is a special application of multivariate analysis of variance (MANOVA) in which several dependent variables are measured and they are all measured on the same scale.

The following Matlab project contains the source code and Matlab examples used for tukey's hsd multiple comparisons test among proportions. . A statistical analysis used for count data is to compare the proportions of a binary outcome of interest for two or more groups.

The following Matlab project contains the source code and Matlab examples used for calculate rationalized arcsine transform. Doing linear tests (like ANOVA or t-tests) on proportional data (values between 0 and 1) is difficult since the distributions of these values are not strictly Gaussian, especially when the proportions are near 0 or 1.

The following Matlab project contains the source code and Matlab examples used for rma1multap. One-sample repeated measures is used to analyze the relationship between the independent variable and dependent variable when:(1) the dependent variable is quantitative in nature and is measured on a level that at least approximates interval characteristics, (2) the independent variable is within-subjects in nature, and (3) the independent variable has three or more levels.

The following Matlab project contains the source code and Matlab examples used for mauchly's sphericity test for orthogonal contrasts. . Other hypothesis used with the Mauchly's sphericity test is on the orthonormalized contrasts, H0: C’SC = s^2I , where C is any full-rank (p-1) x p matrix of orthonormal contrasts.