<p>Reduced mixed-effects model retaining significant predictors of facility delivery (N = 572).</p
<p>Standardized residuals indicating the proximity of each individual subject’s mean latency in the ...
We can observe the very significant impact of the se predictor on the observed outcome.</p
These are testing the effects of the experimental treatments on the pathogens, LBAM, plant health, s...
Model results for the three yield variables in Year 1 against treatments or Plant Health (Percentage...
Logistic mixed-effect models for single predictors (excluding function words).</p
<p>The explanatory variable treatment was removed from the model as it was neither significant as si...
Due to the large data set, all factors are significant. However, we made an arbitrary cut-off at the...
<p>Linear mixed effects models and results for Experiments 1–3 (significant results in bold).</p
Logistic mixed-effect models including all predictors (escluding function words).</p
Result for models of two of the yield variables in Year 2 against pathogen variables. These are the ...
Logistic regression model of the impact of setting, prevention level, and study design on the odds t...
<p>Mixed effects models of clinic-month intervention rates with autoregressive residuals (<i>n</i> =...
Results of Mixed effects Model with naming latencies as the criterion variable and H statistic, age ...
Multivariate regression analysis of predictors of total delivery, by facility type.</p
Mixed-effect modeling is recommended for data with repeated measures, as often encountered in design...
<p>Standardized residuals indicating the proximity of each individual subject’s mean latency in the ...
We can observe the very significant impact of the se predictor on the observed outcome.</p
These are testing the effects of the experimental treatments on the pathogens, LBAM, plant health, s...
Model results for the three yield variables in Year 1 against treatments or Plant Health (Percentage...
Logistic mixed-effect models for single predictors (excluding function words).</p
<p>The explanatory variable treatment was removed from the model as it was neither significant as si...
Due to the large data set, all factors are significant. However, we made an arbitrary cut-off at the...
<p>Linear mixed effects models and results for Experiments 1–3 (significant results in bold).</p
Logistic mixed-effect models including all predictors (escluding function words).</p
Result for models of two of the yield variables in Year 2 against pathogen variables. These are the ...
Logistic regression model of the impact of setting, prevention level, and study design on the odds t...
<p>Mixed effects models of clinic-month intervention rates with autoregressive residuals (<i>n</i> =...
Results of Mixed effects Model with naming latencies as the criterion variable and H statistic, age ...
Multivariate regression analysis of predictors of total delivery, by facility type.</p
Mixed-effect modeling is recommended for data with repeated measures, as often encountered in design...
<p>Standardized residuals indicating the proximity of each individual subject’s mean latency in the ...
We can observe the very significant impact of the se predictor on the observed outcome.</p
These are testing the effects of the experimental treatments on the pathogens, LBAM, plant health, s...
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