A computer-based stepwise multiple regression algorithm is used to develop an equation for predicting the probability of success in two seam-mining situations. The model provides a measure of risk involved in mining multiple seams. The data used to develop the model are from a historical record ...
46,47 In contrast to the brain's explicit learning and reasoning mechanisms, parsimonious variable selection methods like stepwise regression usually fail to select causal features and parameters in historical data due to multicollinearity problems. Because of such multicollinearity error, it is obvious ...
Thus, predicting the likelihood of O-glycosylation with sequence and structural information using classical regression analysis is quite difficult. In particular, if a binary response is used to distinguish between O-glycosylated and non-O- glycosylated sequences, an appropriate set of non-O-glycosyl...
2.Based on this correlation,three stepwise regreession equations and oneREEP(Regression Estimation of Event Probaility)equation have been formulated.在此基础上分别用逐步回归方法及事件概率回归估计方法,建立方程,计算黄海热带气旋发生个数及偏离正常年份的程度,并对各种方法及预报结果进行了分析对比,效果较好。
Then, a backward stepwise multivariate Cox regression was used to determine independent significant prognostic factors. The prediction model was developed based on the factors associated with PFS. A nomogram based on the final model was constructed for visualized prediction of 1-, 2-, and 3-year ...
and PE-related imaging or blood tests. Any remaining missing predictor values in the development data were imputed by use of multiple imputation techniques (e.g. expectation maximization approach). Model variable selection was divided into three steps: Step 1: use stepwise regression to select varia...
Subsequently, multiple forward stepwise logistic regression was conducted on the selected factors from the LASSO regression using the “glm” package [18]. Using the “rms” package in R, nomograms and forest plots were constructed. The 95% confidence intervals (CI) were estimated through 1,000...
Predicting all-cause mortality risk is challenging and requires extensive medical data. Recently, large-scale proteomics datasets have proven useful for predicting health-related outcomes. Here, we use measurements of levels of 4,684 plasma proteins in 2
To structure the regression results, a stepwise approach was taken: First, in order to test the first three research questions (RQ 1a, RQ 1b & RQ 2), the impacts of the indepen- dent variables were examined (blockwise). Second, the interaction effects between HRQoL measures and success ...
If this is the case, you might be more comfortable with one of the multivariate methods implemented in many statistical packages. Two of those methods are stepwise regression and partial least squares regression. View chapter Book 2018, Handbook of Statistical Analysis and Data Mining Applications (...