When repeated measures are used which assumption is violated?


What is a repeated measures factor?

Repeated measures design is a research design that involves multiple measures of the same variable taken on the same or matched subjects either under different conditions or over two or more time periods. For instance, repeated measurements are collected in a longitudinal study in which change over time is assessed.

Is compound symmetry in repeated measures Anova a requirement?

Although compound symmetry has been shown to be a sufficient condition for conducting ANOVA on repeated measures data, it is not a necessary condition. Sphericity is a less restrictive form of compound symmetry.

What is covariance in statistics?

Covariance is a statistical tool that is used to determine the relationship between the movement of two asset prices. When two stocks tend to move together, they are seen as having a positive covariance; when they move inversely, the covariance is negative.

Can covariance matrix negative?

2 Answers. Any negative correlation between two elements will end up with a corresponding negative entry in the covariance matrix. can appear as covariance matrix for any positive eigenvalues 2a, 2b.

When the assumption of sphericity is violated what action is needed?

Answer: 8. When the assumption of sphericity is violated, what action is needed? Correct the model degrees of freedom and correct the error degrees of freedom.

Does negative correlation mean negative covariance?

If two variables move in opposite directions, the covariance and correlation between them is negative. For example, the covariance and correlation between interest rates and new home sales is negative because rising interest rates increase the cost of purchasing a new home, which in turn reduces new home sales.

What is sphericity in repeated measures Anova?

Sphericity is the condition where the variances of the differences between all combinations of related groups (levels) are equal. The violation of sphericity is serious for the repeated measures ANOVA, with violation causing the test to become too liberal (i.e., an increase in the Type I error rate).

Is the inverse of a symmetric matrix symmetric?

Use the properties of transpose of the matrix to get the suitable answer for the given problem. As the inverse of the matrix is unique A−1 is symmetric. Therefore, the inverse of a symmetric matrix is a symmetric matrix.

Why do most assets of the same type show positive covariance of returns with each other?

Why do most assets of the same type show positive covariances of returns with each other? Because their profits and risk factors move together you should expect the stock returns to likewise move together and have high covariance.

How do you interpret covariance?

When a positive number is used to indicate the magnitude of covariance, the covariance is positive. A negative number represents an inverse relationship. The concept of covariance is commonly used when discussing relationships between two economic indicators or terms.

What is the use of covariance matrix?

When the population contains higher dimensions or more random variables, a matrix is used to describe the relationship between different dimensions. In a more easy-to-understand way, covariance matrix is to define the relationship in the entire dimensions as the relationships between every two random variables.

What is compound symmetry?

For example, the Compound Symmetry structure just means that all the variances are equal to each other and all the covariances are equal to each other. That’s it. Each variance and each covariance is completely different and has no relation to the others.

What is the meaning of covariance matrix?

covariance matrix. The mean vector consists of the means of each variable and the variance-covariance matrix consists of the variances of the variables along the main diagonal and the covariances between each pair of variables in the other matrix positions.

Can the covariance be greater than 1?

The covariance is similar to the correlation between two variables, however, they differ in the following ways: Correlation coefficients are standardized. Thus, a perfect linear relationship results in a coefficient of 1. Therefore, the covariance can range from negative infinity to positive infinity.

Are covariance matrices symmetric?

The covariance matrix is always both symmetric and positive semi- definite. mean covariance equal to the covariance of the density p.

What are the assumptions of repeated measures Anova?

Assumptions for Repeated Measures ANOVA

  • Independent and identically distributed variables (“independent observations”).
  • Normality: the test variables follow a multivariate normal distribution in the population.
  • Sphericity: the variances of all difference scores among the test variables must be equal in the population.

How do you interpret a covariance matrix?

In the covariance matrix in the output, the off-diagonal elements contain the covariances of each pair of variables. The diagonal elements of the covariance matrix contain the variances of each variable. The variance measures how much the data are scattered about the mean.

How do you know if sphericity is violated?

If sphericity is violated, then the variance calculations may be distorted, which would result in an F-ratio that is inflated. Sphericity can be evaluated when there are three or more levels of a repeated measure factor and, with each additional repeated measures factor, the risk for violating sphericity increases.

Does covariance of 0 imply independence?

Zero covariance – if the two random variables are independent, the covariance will be zero. However, a covariance of zero does not necessarily mean that the variables are independent. A nonlinear relationship can exist that still would result in a covariance value of zero.

What is covariance matrix example?

Square, add them up, and divide by n-1. For example, for X: Var(X) = [ (64–68.0)^2 + (66–68.0^2 + (68-68.0)^2 + (69-68.0)^2 +(73-68.0)^2 ] / (5-1) = (16.0 + 4.0 + 0.0 + 1.0 + 25.0) / 4 = 46.0 / 4 = 11.50.

What is the difference between homogeneity of variance and sphericity?

I believe sphericity refers to equality in variance across the different repeated measures, whereas homogeneity of variance (assuming that is what you’re asking about) refers to homogeneity of variance in the dependent variables in a single measure across different levels of the independent variables.

What is difference between correlation and covariance?

Covariance indicates the direction of the linear relationship between variables. Correlation on the other hand measures both the strength and direction of the linear relationship between two variables.

Is repeated measures an experimental design?

Repeated Measures design is an experimental design where the same participants take part in each condition of the independent variable. This means that each condition of the experiment includes the same group of participants. Repeated Measures design is also known as within groups, or within-subjects design.

Is covariance non negative?

Unlike Variance, which is non-negative, Covariance can be negative or positive (or zero, of course). A positive value of Covariance means that two random variables tend to vary in the same direction, a negative value means that they vary in opposite directions, and a 0 means that they don’t vary together.

What is a three way repeated measures Anova?

The repeated-measures ANOVA is used for analyzing data where same subjects are measured more than once. three-way repeated measures ANOVA used to evaluate simultaneously the effect of three within-subject factors on a continuous outcome variable.