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- Generalized linear mixed model fit by maximum likelihood (Laplace Approximation) ['glmerMod']
- Family: binomial ( logit )
- Formula: survival ~ tree + (1 | tree/rep)
- Data: NPV01Datacorr.data
- Control: glmerControl(optimizer = "bobyqa")
- ...
- Fixed effects:
- Estimate Std. Error z value Pr(>|z|)
- (Intercept) -0.09531 0.17837 -0.534 0.59311
- treeBC3F3 0.84765 0.26019 3.258 0.00112 **
- treeD54 -0.40113 0.24606 -1.630 0.10305
- treeD58 -0.76691 0.26314 -2.914 0.00356 **
- treeEllis1 -0.38426 0.25090 -1.532 0.12563
- treeQing 0.53357 0.24338 2.192 0.02836 *
- ---
- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
- levels(NPV01Datacorr.data$tree)
- [1] "Ash" "BC3F3" "D54" "D58" "Ellis1" "Qing"
- contrastmatrix <- rbind(c(-0.5, 0, 0.5, 0.5, -0.5, 0), c(0, 0, 0.5, 0.5, -1, 0))
- rownames(contrastmatrix) <- c("Transgenic - Wildtype", "Transgenic - Isogenic")
- summary(glht(NPVcorrbinary.glmer, linfct=mcp(tree=contrastmatrix)))
- Simultaneous Tests for General Linear Hypotheses
- Multiple Comparisons of Means: User-defined Contrasts
- Linear Hypotheses:
- Estimate Std. Error z value Pr(>|z|)
- Transgenic - Wildtype == 0 -0.3919 0.1797 -2.181 0.0459 *
- Transgenic - Isogenic == 0 -0.1998 0.2183 -0.915 0.4866
- (D54 estimate(0.5)) + (D58 estimate(0.5)) + (Intercept estimate(-0.5)) + (Ellis1 estimate(-0.5))
- (-0.40113(0.5)) + (-0.76691(0.5)) + (-0.9531(-0.5)) + (-0.38426(-0.5))
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