nlme

[…] fit quality. We reported the correlation coefficient between explanatory variables in Supplementary Material (Tables  and Table ). Analyses were performed using the package “adehabitatHR”, “sp” and “nlme” from R software. […]

[…] . It also allows the use of every detected perforator separately without averaging per subject, increasing the degrees of freedom (, , ). The LME model was fitted and tested for significance with the NLME package (R Core Team) in R (R Foundation for Statistical Computing).Since the MCA data consists of only the subject level, the LME model collapses to ordinary least squares. Therefore, the flow r […]

[…] the same sample sizes due to missing values or drop outs. All statistical analyses were conducted in the R (www.r-project.org); mixed-effect models for longitudinal analyses were conducted using the nlme package in the R. All methods were performed in accordance with the relevant guidelines and regulations. […]

[…] ant samples. To account for this, we used a linear mixed model with a temporal autocovariate (Turchin ). Linear mixed models were built separately for each principal component. The function lme() in “nlme” package (Pinheiro et al. ) implemented in R (R Core Team ) was used for this purpose. […]

[…] Data from the Stroop test and Sternberg paradigm were analysed using R (www.r-project.org). Response time analyses were performed using the nlme package, which implements mixed effect models and yields t statistics. Accuracy analyses were performed using the lme4 package, which implements mixed effect models for data with a binomial outco […]

[…] e between high and low density, defined as the total number of days from first-instar larva to adult, was quantified using a linear mixed effects model with replicate as a random intercept (R package nlme []). The probability of survival was analyzed using a binomial-distributed generalized linear mixed effects model (GLMM), also with replicate as a random intercept (R package lme4 []). Analyses w […]