Results from larval rearing bioassays were analyzed with a generalized linear mixed model in SAS (PROC GLIMMIX, version 9.4; SAS Institute Inc. Cary, NC, USA). A binomial distribution was used as the response variable was binary; live or dead. Treatment was used as the fixed effect and grafting day as random effect. Post hoc pairwise comparisons of survival between treatments were performed using the Least Squares Means difference.
Mortality data from adult bee dose response bioassays was analyzed using generalized linear models (GLMs) with a log-probit transformation to calculate LD50 values and 95% confidence intervals [38 (link),53 ]. Pairwise tests were used to compare treatments and assess interactive effects between test chemical combinations. A test of parallelism was used to assess differences in the slope of the dose-response. A test of equality was used to assess differences between dose-response in one treatment relative to another. Statistical analysis of the results from adult assays was performed in R (version 3.4.2, R Foundation for Statistical Computing, Vienna, Austria).
Mortality data from adult bee dose response bioassays was analyzed using generalized linear models (GLMs) with a log-probit transformation to calculate LD50 values and 95% confidence intervals [38 (link),53 ]. Pairwise tests were used to compare treatments and assess interactive effects between test chemical combinations. A test of parallelism was used to assess differences in the slope of the dose-response. A test of equality was used to assess differences between dose-response in one treatment relative to another. Statistical analysis of the results from adult assays was performed in R (version 3.4.2, R Foundation for Statistical Computing, Vienna, Austria).
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