Using Simulation to Test the Reliability of Regression Models

Abstract

In many sciences, it is standard laboratory practice to use a statistical design of experiment and a regression model to study the influence of multiple parameters under a wide range of conditions. The current study aims at investigating the reliability of regression models by examining recently published models. Of particular interest are the assumptions that are not robust to violation such as the reliability of measurements, constant variation of residuals, and sample size. To test regression models simulation is used to model potential measurement error and the importance of sample sizes on parameter estimation. The randomly perturbed designs are then used together with associated mathematical models obtained from the original designs to simulate experiments and obtain new regression models. A comparison of the original model to the new model, and various statistical tests are performed to determine how accurate the original parameters have been predicted when exposed to simulated measurement error.

Efek Besaran Simpangan Baku Sampel terhadap Nilai Residu dalam Analisis Regresi Berganda Tiga Variabel Bebas

“…Penelitian ini merupakan penelitian deskriptif dengan menggunakan data simulasi yang diadakan menggunakan program SPSS. Data simulasi dapat digunakan untuk menguji suatu konsep pada analisis regresi atau analisis statistik lainnya (Rispoli & Shah, 2015). Setelah pengadaan data simulasi kemudian dilakukan modifikasi besaran dan susunan data pada setiap variabel untuk memenuhi persyaratan analisis regresi berganda antara lain normalitas, linearitas, multikolinearitas, dan heteroskedastisitas.…”