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Full-Text Articles in Physical Sciences and Mathematics
Genetic Variants In Kcnj11, Tcf7l2 And Hnf4a Are Associated With Type 2 Diabetes, Bmi And Dyslipidemia In Families Of Northeastern Mexico: A Pilot Study, Hugo Leonid Gallardo-Blanco, Jesus Zacarias Villarreal-Perez, Ricardo Martin Cerda-Flores, Andres Figueroa
Genetic Variants In Kcnj11, Tcf7l2 And Hnf4a Are Associated With Type 2 Diabetes, Bmi And Dyslipidemia In Families Of Northeastern Mexico: A Pilot Study, Hugo Leonid Gallardo-Blanco, Jesus Zacarias Villarreal-Perez, Ricardo Martin Cerda-Flores, Andres Figueroa
Computer Science Faculty Publications and Presentations
The aim of the present study was to investigate whether genetic markers considered risk factors for metabolic syndromes, including dyslipidemia, obesity and type 2 diabetes mellitus (T2DM), can be applied to a Northeastern Mexican population. A total of 37 families were analyzed for 63 single nucleotide polymorphisms (SNPs), and the age, body mass index (BMI), glucose tolerance values and blood lipid levels, including those of cholesterol, low‑density lipoprotein (LDL), very LDL (VLDL), high‑density lipoprotein (HDL) and triglycerides were evaluated. Three genetic markers previously associated with metabolic syndromes were identified in the sample population, including KCNJ11, TCF7L2 and HNF4A. The KCNJ11 …
The Effect Of Ignoring Statistical Interactions In Regression Analyses Conducted In Epidemiologic Studies: An Example With Survival Analysis Using Cox Proportional Hazards Regression Model, Kristina Vatcheva, Joseph B. Mccormick, Mohammad H. Rahbar
The Effect Of Ignoring Statistical Interactions In Regression Analyses Conducted In Epidemiologic Studies: An Example With Survival Analysis Using Cox Proportional Hazards Regression Model, Kristina Vatcheva, Joseph B. Mccormick, Mohammad H. Rahbar
School of Mathematical and Statistical Sciences Faculty Publications and Presentations
Objective: To demonstrate the adverse impact of ignoring statistical interactions in regression models used in epidemiologic studies.
Study design and setting: Based on different scenarios that involved known values for coefficient of the interaction term in Cox regression models we generated 1000 samples of size 600 each. The simulated samples and a real life data set from the Cameron County Hispanic Cohort were used to evaluate the effect of ignoring statistical interactions in these models.
Results: Compared to correctly specified Cox regression models with interaction terms, misspecified models without interaction terms resulted in up to 8.95 fold bias in estimated …