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Knowledge of interrelationships between grain yield and its contributing components will improve the efficiency of breeding programs through the use of appropriate selection indices. Previous path analyses studies in maize (Zea mays L.) treated yield components as first‐order variables. The present study, based on evaluation of 90 experimental maize hybrids (comprising one diallel and one line × tester set) at two locations in India, utilizes a sequential path model for analysis of genetic associations among grain yield and its related traits by ordering the various variables in first‐, second‐, and third‐order paths on the basis of their maximum direct effects and minimal collinearity. The sequential path model showed distinct advantages over the conventional path model in discerning the actual effects of different predictor variables. Two first‐order variables, namely 100‐grain weight and total number of kernels per ear …