Biomedical subjects
Publications and source records attributed to K Singhal.
Statistical methods were used to calculate the possible observer error in measuring cup migration in bipolar hip arthroplasty from follow-up radiographs. Finding the "tolerance limits" by such methods helped in assigning the true significance of any observed change.
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Regression and clustering methods have both been used to explore the effects of explanatory variables on survival times for patients with cancer or other chronic diseases. This paper discusses effective and computationally feasible approaches for this task in situations where there are fairly large and complex data sets; the techniques stressed are all-subsets regression and a kind of recursive partition clustering. We compare the two approaches in a rather general way, in part by examining some survival data for patients with ovarian carcinoma, and conclude that both have strong points to recommend them.
This paper describes a system written to carry out regression analyses under certain generalized linear models that are widely used in biomedical research. These include continuous response models such as the Weibull, log-logistic, log-normal and Cox proportional hazards models used in survival analysis, and also discrete Poisson, binomial and multinomial response regression models. The system fits models, generates residuals and other diagnostic output, and has an all-subsets regression feature. This paper describes the models implemented and gives statistical background; Part II describes the ISMOD system and presents examples of its application.
This paper describes a system written to carry out regression analyses under certain generalized linear models that are widely used in biomedical research. These include continuous response models such as the Weibull, log logistic, log normal and Cox proportional hazards models used in survival analysis, and also discrete Poisson, binomial and multinomial response regression models. The system fits models, generates residuals and other diagnostic output, and also has an all-subsets regression feature. This paper describes the ISMOD system and presents examples of its application; Part I describes the models implemented and gives statistical background.
Explore the source record for details and available documents.
Explore the source record for details and available documents.
Explore the source record for details and available documents.