Sentence examples for using a generalised linear from inspiring English sources

Curves were estimated using a generalised linear model (glm) with a binomial distribution and a "probit" link function.

The relationship between community level (asexual parasite) PCR prevalence and the proportion of patent and subpatent individuals with PCR-detectable gametocytes as assessed using a generalised linear mixed effects model with asexual parasite prevalence as a fixed effect and study as a random effect.

The outputs from models fitted using a Generalised Linear Model approach were then incorporated into an individual-based simulation model of plant spread to investigate the invasion potential in different habitats using a factorial design of treatments.

We attempted to re-estimate the equation using the patient level data from Study 1033, using a generalised linear model in R to map the EQ-5D-3 L utility to the PAC-QOL overall score.

The detached needle assay was analysed using a generalised linear mixed model (GLMM) with binomial errors (R-package lme4) testing for differences in the proportion of needle lesions between the uninoculated control and the samples inoculated with 3 isolates of Phytophthora pluvialis.

We then determined the proportion of the carapace that was coloured and examined its relationship with carapace size and sex using a generalised linear model.

The effects of pollinator exclusion on pollination success were analysed using a generalised linear model with log-transformed calyx diameter and mesh bag treatment as fixed explanatory variables.

Log linear analysis uses a generalised linear model, which estimates the cell counts of a Table, using different combinations of the margins.

Pooled data used a generalised linear model with Poisson distribution and overdispersion parameter (JMP7 software, e-academy Inc).

This was done using generalised estimating equations (GEE), which incorporates species relatedness as a correlation matrix and uses a generalised linear model approach, which allows data to be analysed using non-normal response variables.

In all three cases we used a generalised linear model with binomial errors.