A comparison of factor‐analytic and equal diagonal factor‐analytic models in multi‐location trials analyses. (9th May 2020) - Hu, Xiyuan; Han, Dejun; Zhang, Renhe; Wu, Jianhui; Ren, Huili
Abstract: The two most promising models for analyzing multi‐location trials (MLT) include the factor‐analytic (FA) and equal diagonal factor‐analytic (FA1) models. Here, we compare the two models by analyzing four datasets performed for the corn (Zea mays L.) performance trails in Northeastern and Northern China. The FA model contained more parameters for the variance–covariance of variety effects than the FA1 model. In data fitting, the effective (parameter value estimated >0) parameter number difference between the two models was not as large as in theory and was reduced with an increasing number of factors. In goodness‐of‐fit for trial data, the two models were competitive based on both the Akaike Information Criterion (AIC) and the likelihood‐ratio test (LRT). There were no notable differences between the two models in the estimates, rankings, standard errors of estimates, test efficiencies of contrasts for variety main (mean over all locations) effects, and discrimination power for varieties. The FA models were superior to FA1 models in the standard error of estimates and test efficiency of contrasts for variety simple effects. Therefore, the FA model was suggested for the analysis of MLTs. A general recommendation for the selection of either the FA or FA1 models using AIC or LRT cannot be made from this analysis.