Andrew
J. Bohonak
San Diego State University
RMA is a fast and simple application for reduced major axis regression (RMA). RMA is more appropriate than standard ordinary least squares (OLS) regression when the independent variable x is measured with error (see Sokal and Rohlf, Biometry ). McArdle (1988) suggests as a rule of thumb that RMA should be used when the error rate in x exceeds onethird of the error rate in y.
The RMA application estimates error for the slope and intercept of RMA regression using three methods:
For population genetic applications of reduced major axis regresssion, see IBDWS.
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