Weighted regression analysis for comparing varietal adaptation

The normally used joint linear regression analysis (OLS) is not appropriate for comparing estimates of stability parameters of varieties when the error variances of site means are heterogeneous. Weighted regression analysis (WLS), in these situations, yields more precise estimates of stability parameters. A comparison of the two analytical methods using the grain yield (kg ha(-1)) data of 12 varieties and one hybrid of pearl millet [Pennisetum typhoides (Burm.) S. & H.], tested at 26 sites in India, revealed that the weighted regression analysis yields more efficient estimates of regression coefficients (b i ) than the ordinary regression analysis, and that the standard errors of b i values were reduced by up to 43%. The estimated b i differed with the two procedures. The number of varieties with b i ssignificantly deviating from unity was not only more (five varieties) with weighted regression analysis than the ordinary regression analysis (one variety), but the classification of varieties as possessing general or specific adaptation differed with the two procedures.