The Wald-Wolfowitz runs test can assess the correctness of a regression curve fitted to a data set with one independent parameter. The assessment is performed through examination of the residuals, where the signs of the residuals would appear randomly if the regression curve were correct. We propose extending the test to the case where multiple data points were measured for specific independent parameter values. By randomly permutating the data points corresponding to each independent parameter value and treating their residuals as occurring in their permutated sequence and then executing the runs test, results are shown to be equivalent to those of a data set containing the same number of points with no repeated measurements. This approach avoids the loss of points, and hence loss of test sensitivity, were the means at each independent parameter value used. It also avoids the problem of weighting each mean differently if the number of data points measured at each parameter value is not identical.
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