Sentence examples for regression effect on from inspiring English sources

The final regression model used was: Where Y1 is the prevalence of infection on the farm i (i = 1-12), B 0 is the intercept, B i is the regression effect on masl of farm pastures i (x = 0-600) and e i is the random residual error.

Possible effects of prophylactic treatment, farmer's perception of ticks on pastures and masl of pastures (as regression effect) on the flock's prevalence of infection, direct losses on summer pasture and weaning weight was analyzed using the General Linear Model method of the GLM procedure in SAS [ 24].

The forest plot in Fig. 4 displays for each country the 95% confidence interval around b TICS (within), their within-country regression effect of TICS on science achievement.

Similarly, students in schools that have high implementation of the TIMSS curriculum are expected to perform well (i.e., within-country regression effect of TICS on achievement: b TICS (within)  > 0 for all countries).

The authors used a representative community sample to compare the regression effects of insurance coverage on utilization of mental health services among these subjects.

Table 1 contains observed odds ratios for the simulated data set and their decomposition into regression effects based on SEM using Yule's transformation of odds ratios.

The genetic associations with fat-free mass index were weaker and the quantile regression effects less pronounced than those on fat mass index.

For the meta-regression, effect size was regressed on the quality score with the aim of accounting for the heterogeneity through differences in quality score.

Effects on individual, team, and organizational proactivity were examined with OLS regression analyses, effects on ideas for improvement with logistic regression.

Effects on binary outcomes were assessed with logistic regression, and effects on continuous outcomes by ordinary least squares linear regression, logarithmically transformed to obtain a near normal distribution.

This reduction of the number of false positives in the linear regression has much effect on the performance of the VAR model which is equivalent to m linear regressions.