Binary logistic regression using one response variable can be developed into a binary logistic regression model with two response variables namely bivariate logistic regression (BLR). This research is focused on developing a second-order bivariate binary logistic regression model for the independent ...
The main aim of this study is to use weights of evidence (WoE), logistic regression (LR), naïve Bayes (NB), and alternating decision tree (ADTree) mod
In addition to bivariate statistics for continuous measures, the continuous preoperative and operative variables were correlated to binary categorical measures. This was done using unpaired Studentt-tests to compare studies either meeting or not meeting PASS orMCID. ...
Paired binary data often appear in studies of subjects with two sites such as eyes, ears, lungs, kidneys, feet and so on. Three popular models [i.e., (Rosn
studies that researched this association have only analysed the data descriptively, without taking into account the effect of potential outliers. This study aimed to examine the presence and impact of outlier women on the relationship between female education and fertility in Malawi, using regression ...
Bivariate and binary logistic regression analyses were used to identify predictors of infection. The overall prevalence of UGS in Likomba, Holforth-Likomba ... AE Green,JK Anchang-Kimbi,GB Wepnje,... - 《Infectious Diseases of Poverty》 被引量: 0发表: 2021年研究...
Nigeria. They concluded that based on the area under the curve (AUC) measure, EBF, as a data driven technique, outperformed the AHP. Chenini and Msaddek36compared the bivariate statistical analysis and logistic regression model (LR) to produce a GWRP map in Qued Guenniche in the north of...
Bivariate logistic regression: modelling the association of small for gestational age births in twin gestations bivariate binary responses,and (ii) modelling the odds ratio describing the pairwise association between the two binary responses in relation to several ... CV Ananth,JS Preisser - 《Statist...
Bivariate binary dataCentered autologistic modelsSpatial dependenceConditional autoregressive (CAR) modelMarkov random field (MRFSpatial regression for binary dataDiscrete index random fieldSpatially structured discrete data arise in diverse areas of application, such as forestry, epidemiology, or soil sciences...
[27], where authors employ a bivariate neural network model,RankProb, that estimates the probability that one item is more relevant than the other.RankProbestimates the probability that one item is more likely being relevant than the other one. This problem is addressed as a binary ...