Growth curve models for the analysis of longitudinal data often involve many parameters, which may be the cause of loss of efficiency in the inference or poor interpretation of the results of analysis. This paper proposes to introduce a family of linear structures into the fixed location parameters and the variance-covariance parameters in growth curve models. This leads to the models with fewer unknown paremeters, resulting in increased efficiency and easier interpetation in analysis. A noniterative algorithm is also provided for estimating unknown parameters in the model.