Variables (excluding comorbid conditions) were considered for inclusion in the multivariate linear regression model if univariate screening p value was less than 0.25 and were ultimately included in the model if the adjusted p value was less than 0.05.
Infection status for all 3 species of trypanosome and other variables with p < 0.25 in initial univariable screening were considered for inclusion in the multivariable linear regression model, built using backward elimination procedures.
Next, the job factors, organisational factors and respondent characteristics with P < 0.01 in the univariate regression analysis were selected as independent variables for inclusion in the multiple linear regression analysis.
For inclusion of calibrators in the linear range of the sensor, replicate calibration standards were required to produce a precision of ≤20% RSD and accuracy of 100 ± 20%.
Variables having a relatively low correlation with other predictor variables and a significant association with ECAT (p < 0.10) were selected for inclusion in the final multiple linear regression model (Table 2).
For the RO-RO SSS volume on the other hand, the total number of SSS ports is more relevant as indicated by its inclusion in the multivariate linear regression model for RO-RO SSS volume.
The column marked with "√" indicates inclusion in the final linear model.
Variables of sufficient potential interest to warrant inclusion in the multiple linear regression models had a p-value < 0.20 [ 21].
The variables having a P value <0.05 in univariate t-test were selected for inclusion in multivariate linear regression model analyses.
Geographic variables of emissions and land use derived using GIS were treated as candidate predictors and were grouped into emissions-based categories and tested for inclusion in a linear regression model using forward stepwise selection.
