What is analysis of covariance?
Analysis of covariance (ANCOVA) is a method for comparing sets of data that consist of two variables (treatment and effect, with the effect variable being called the “variate”) when a third variable (called the “covariate”) exists. This covariate can be measured but not controlled and has a definite effect on the variable of interest.
Is analysis of covariance biased if the groups are not equal?
The case for preferring analysis of covariance (ANCOVA) to the simple analysis of change scores (SACS) has often been made. Nevertheless, claims continue to be made that analysis of covariance is biased if the groups are not equal at baseline. If the required equality were in expectation only, this …
What is the concentration of tetrabromobenzene?
Hexabromobenzene, pentabromobenzene, and 1,2,4,5-tetrabromobenzene were detected at concentrations of 2.1 to 4.1 ng/g. 1,2,4,5-Tetrabromobenzene was found in largest amount]
Where is hexabromobenzene found in the human body?
The concn of hexabromobenzene was highest in the fat. The compound was present in the maternal liver, brain, heart, kidney, and spleen, as well as in fetal tissue. Reported that fat was the only tissue in which the concentration showed a dose response relationship.
What is the error covariance matrix for linear regression?
The regression relationship between the dependent variable and concomitant variables must be linear. The error is a random variable with conditional zero mean and equal variances for different treatment classes and observations. The errors are uncorrelated. That is, the error covariance matrix is diagonal.
How to interpret the results of a randomized controlled experiment with covariance?
In a randomized experiment in which the covariate is measured afterthe treatment has been applied and has affected the covariate, interpreting the results of an analysis of covariance is difficult at best. In this situation the expected values of the group covariate means are not equal, even though the subjects were assigned randomly.
Why do we measure body weight covariate in animal studies?
We usually wish to evaluate the effect of dose or exposure level on the specific organ weights, but most organ weights also increase in proportion to increase in animal body weight. Because primary interest is not in the effect of the body weight covariate, it is measured to allow for adjustment.