Influential data points can affect the results of
a regression analysis; for example, the usual summary
statistics and tests of significance may be
misleading. The importance of regression
diagnostics in detecting influential points is
discussed, and five statistics are recommended for
the applied researcher. The suggested diagnostics
were used on a small dataset to detect an influential
data point, and the effects were analyzed.
Colinearity-based diagnostics also are discussed
and illustrated on the same dataset. The nonrobustness
of the least squares estimates in the
presence of influential points is emphasized.
Diagnostics for multiple influential points, multivariate
regression, multicolinearity, nonlinear
regression, and other multivariate procedures also
are discussed. Index terms: Andrew-Pregibon
measure, colinearity, Cook’s distance, covariance
ratio, influential observations, measurement error,
partial residual plot, regression diagnostics.
Chatterjee, Sangit & Yilmaz, Mustafa. (1992). A review of regression diagnostics for behavioral research. Applied Psychological Measurement, 16, 209-227. doi:10.1177/014662169201600301
Chatterjee, Sangit; Yilmaz, Mustafa.
A review of regression diagnostics for behavioral research.
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