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OrganisationName: Ctsi Bread UCSF
OrganisationURL: http://ctsi.ucsf.edu
Country: USA

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There are three conceptual classes of such models: 1. Fixed-effects models assumes that the data came from normal populations which may differ only in their means. (Model 1) 2. Random effects models assume that the data describe a hierarchy of different populations whose differences are constrained by the hierarchy. (Model 2) 3. Mixed-effect models describe situations where both fixed and random effects are present. (Model 3) In practice, there are several types of ANOVA depending on the number of treatments and the way they are applied to the subjects in the experiment: * One-way ANOVA is used to test for differences among two or more independent groups. Typically, however, the One-way ANOVA is used to test for differences among three or more groups, with the two-group case relegated to the t-test (Gossett, 1908), which is a special case of the ANOVA. The relation between ANOVA and t is given as F = t ². * One-way ANOVA for repeated measures is used when the subjects are subjected to repeated measures; this means that the same subjects are used for each treatment. Note that this method can be subject to carryover effects. * Factorial ANOVA is used when the experimenter wants to study the effects of two or more treatment variables. The most commonly used type of factorial ANOVA is the 2×2 (read: two by two) design, where there are two independent variables and each variable has two levels or distinct values. Factorial ANOVA can also be multi-level such as 3×3, etc. or higher order such as 2×2×2, etc. but analyses with higher numbers of factors are rarely done because the calculations are lengthy and the results are hard to interpret. * When one wishes to test two or more independent groups subjecting the subjects to repeated measures, one may perform a factorial mixed-design ANOVA, in which one factor is independent and the other is repeated measures. This is a type of mixed effect model. * Multivariate analysis of variance (MANOVA) is used when there is more than one dependent variable.

There are three conceptual classes of such models:
1. Fixed-effects models assumes that the data came from normal populations which may differ only in their means. (Model 1)
2. Random effects models assume that the data describe a hierarchy of different populations whose differences are constrained by the hierarchy. (Model 2)
3. Mixed-effect models describe situations where both fixed and random effects are present. (Model 3)
In practice, there are several types of ANOVA depending on the number of treatments and the way they are applied to the subjects in the experiment:
* One-way ANOVA is used to test for differences among two or more independent groups. Typically, however, the One-way ANOVA is used to test for differences among three or more groups, with the two-group case relegated to the t-test (Gossett, 1908), which is a special case of the ANOVA. The relation between ANOVA and t is given as F = t ².
* One-way ANOVA for repeated measures is used when the subjects are subjected to repeated measures; this means that the same subjects are used for each treatment. Note that this method can be subject to carryover effects.
* Factorial ANOVA is used when the experimenter wants to study the effects of two or more treatment variables. The most commonly used type of factorial ANOVA is the 2×2 (read: two by two) design, where there are two independent variables and each variable has two levels or distinct values. Factorial ANOVA can also be multi-level such as 3×3, etc. or higher order such as 2×2×2, etc. but analyses with higher numbers of factors are rarely done because the calculations are lengthy and the results are hard to interpret.
* When one wishes to test two or more independent groups subjecting the subjects to repeated measures, one may perform a factorial mixed-design ANOVA, in which one factor is independent and the other is repeated measures. This is a type of mixed effect model.
* Multivariate analysis of variance (MANOVA) is used when there is more than one dependent variable.

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FirstName	Ctsi
LastName	Bread
Title	Administrator
Telephone	415.502.7893
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Email	ctsibread@ucsfmedctr.org
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Team	BREAD
Organization	UCSF CTSI
Location	San Francisco, CA
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