Estimating the confidence interval of the regression coefficient of the blood sugar model through a multivariable linear spline with known variance

Anna Islamiyati; Raupong Raupong; Kalondeng Anisa; Ummi Sari

doi:10.21307/stattrans-2022-012

Estimating the confidence interval of the regression coefficient of the blood sugar model through a multivariable linear spline with known variance

Anna Islamiyati Department of Statistics, Faculty of Mathematics and Natural Sciences, Hasanuddin University, Indonesia. ORCID:https://orcid.org/0000-0001-6441-0306 , Raupong Raupong Department of Statistics, Faculty of Mathematics and Natural Sciences, Hasanuddin University, Indonesia. , Kalondeng Anisa Department of Statistics, Faculty of Mathematics and Natural Sciences, Hasanuddin University, Indonesia. , Ummi Sari Hasanuddin University Teaching Hospital, Indonesia. Statistics in Transition new series, vol. 23, 2022, 1, pages: 201–212 Published online: 15 March 2022 DOI 10.21307/stattrans-2022-012 Citation: Islamiyati A., Raupong , Anisa K., Sari U., (2022). Estimation the confidence interval of the regression coefficient of the blood sugar model through multivariable linear spline with known variance, Statistics in Transition new series, 23(1), pp. 201–212. https://doi.org/10.21307/stattrans-2022-012

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ABSTRACT

Estimates from confidence intervals are more powerful than point estimates, because there are intervals for parameter values used to estimate populations. In relation to global conditions, involving issues such as type 2 diabetes mellitus, it is very difficult to make estimations limited to one point only. Therefore, in this article, we estimate confidence intervals in a truncated spline model for type 2 diabetes data. We use a non-parametric regression model through a multi-variable spline linear estimator. The use of the model results from the irregularity of the data, so it does not form a parametric pattern. Subsequently, we obtained the interval from beta parameter values for each predictor. Body mass index, HDL cholesterol, LDL cholesterol and triglycerides all have two regression coefficients at different intervals as the number of the found optimal knot points is one. This value is the interval for multivariable spline regression coefficients that can occur in a population of type 2 diabetes patients.

KEYWORDS

confidence interval, diabetes, known variance, spline.

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