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首页> 外文期刊>genetic epidemiology >General purpose model and a computer program for combined segregation and path analysis (SEGPATH): Automatically creating computer programs from symbolic language model specifications
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General purpose model and a computer program for combined segregation and path analysis (SEGPATH): Automatically creating computer programs from symbolic language model specifications

机译:General purpose model and a computer program for combined segregation and path analysis (SEGPATH): Automatically creating computer programs from symbolic language model specifications

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AbstractA general purpose model and a flexible computer program, called SEGPATH, have been developed to assist in the creation and implementation of a variety of genetic epidemiological models. SEGPATH is a computer program which can be used to generate programs to implement linear models for pedigree data, based upon a flexible, model‐specification syntax. SEGPATH models can perform segregation analysis, path analysis, or combined segregation and path analysis using any user‐specified path model and can be structured to analyze any number of multivariate phenotypes, environmental indices, and/or measured covariate fixed effects (including measured genotypes). Population heterogeneity models, repeated‐measures models, longitudinal models, auto‐regressive models, developmental models, and gene‐by‐environment interaction models can all be created under SEGPATH. Pedigree structures can be defined to be arbitrarily complex, and the data analyzed with programs generated by SEGPATH can have any missing value structure, with entire individuals missing, or missing on one or more measurements. Corrections for ascertainment can be done on a vector of phenotypes and/or other measures. Because the model specification syntax is general, SEGPATH can also be used in non‐genetic applications where there is a hierarchical structure, such as longitudinal, repeated‐measures, time series, or nested models. A variety of applications are demonstrated. © 1995

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