Design of experiments

Tukey's test of additivity for a two-way classification analysis of variance. in matlab

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.

Power estimation of a performed z test about mean(s). in matlab

The following Matlab project contains the source code and Matlab examples used for power estimation of a performed z test about mean(s). . Estimates the statistical power of a performed Z test about mean(s). It recalls you the statistical result of the test you should have arrived. It only needs the Z statistic, specified direction and significance level (default = 0.05).

Power1var in matlab

The following Matlab project contains the source code and Matlab examples used for power1var. Besides the power estimation it makes the hypothesis testing concerning the one-sample variance. The function only needs the sample variance, the sample size, the hypothesized value and the significance level.

O'brien's test for homogeneity of variances. in matlab

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.

Computing of a standard (simple) split-plot design analysis of variance. in matlab

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,.

Computes a two-way multivariate analysis of variance for equal or unequal sample sizes. in matlab

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.

Identification of outliers in a one-way analysis of variance model ii (random effects). in matlab

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.

Robust experimental designs for generalized linear models in matlab

The following Matlab project contains the source code and Matlab examples used for robust experimental designs for generalized linear models. Optimal experimental designs for generalized linear models (GLM) depend on the unknown coefficients, and two experiments having the same model but different coefficient values will typically have different optimal designs.

Testing for curvature of a 2^2 factorial design analysis. in matlab

The following Matlab project contains the source code and Matlab examples used for testing for curvature of a 2^2 factorial design analysis. . This m-file is used in experiments where there is uncertain about the assumption of linearity over the region of exploration, and when the experimenter decides to conduct a 2^2 factorial design with a single or several replicates of each factorial run, augmented with some center points.

Rma1multap in matlab

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.

Determines the post-hoc statistical power of a performed analysis of variance model ii (random-effec in matlab

The following Matlab project contains the source code and Matlab examples used for determines the post-hoc statistical power of a performed analysis of variance model ii (random-effec . Estimates the statistical power of an analysis of variance Model II (random-effects) after it has been performed. It requires the observed F-statistic value, numerator degrees of freedom, denominator degrees of freedom and significance level.

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