The sequential regression methodology was applied.
Three logit models with a sound predictability and model fit were established using logistic sequential regression.
It is also known as the fully conditional specification and sequential regression multivariate imputation (White et al., 2011).
Therefore, this study aimed at comparing Adaptive Neuro-Fuzzy Inference System (ANFIS -based subtrANFIS -basedering algorithm with different inputsubtractiveons as well as sequential regression models for simulation of variations in soil clustering
To assess whether incorrect trials were marked by different action dynamics, we conducted an additional analysis using a sequential regression model for each dependent measure.
Based on sequential regression, the positive response of the total number of arthropods to both plant diversity and % cover (Table 4) was driven by the combined influence of at least 5 taxa.
The AIC from sequential regression models was also used to determine if there exists a threshold of temperature or relative humidity above or below which there was no effect on norovirus reports.
The sequential regression model starts with the prediction of height.
Third, sequential regression analyses were conducted in SAS.
Based on a hypothesised order of importance of explanatory variables, manual sequential regression models were analysed.
