[英]FDR correction - extracting p-values from lmer() and creating vectors for use in p.adjust in R
[英]R: how to extract list of covariate p-values from a regression results of an lmer() model?
我有一个混合 lmer model 和 8 个预测变量的示例,我想提取协变量的名称、它们的系数、它们的标准误差和它们的 p 值,并将它们放入矩阵中,以便我可以将它们写出到 a.csv。
我已经将前 3 个提取到列中,但我不知道如何提取 p 值。 你怎么做到这一点? 它是 vcov 还是 getME() 的变体?
这是 model 和摘要的样子:
mod <- lmer(outcome ~ predictor1 + etc...
summary(mod)
Generalized linear mixed model fit by the Laplace approximation
Formula: Freq ~ pm.lag0 + pm.lag1 + pm.lag2 + pm.lag3 + pm.lag4 + pm.lag5
+ temp13 + temp013 + rh13 + rh013 + (1 | county)
Data: dt
AIC BIC logLik deviance
3574 3636 -1775 3550
Random effects:
Groups Name Variance Std.Dev.
county (Intercept) 1.6131 1.2701
Number of obs: 1260, groups: county, 28
Fixed effects:
Estimate Std. Error z value Pr(>|z|)
(Intercept) 2.9356504 0.2614892 11.227 < 2e-16 ***
pm.lag0 0.0012996 0.0005469 2.376 0.017494 *
pm.lag1 0.0005021 0.0005631 0.892 0.372568
pm.lag2 0.0009126 0.0005596 1.631 0.102893
pm.lag3 -0.0007073 0.0005678 -1.246 0.212896
pm.lag4 0.0031566 0.0005316 5.939 2.88e-09 ***
pm.lag5 0.0019598 0.0005359 3.657 0.000255 ***
temp13 -0.0028040 0.0007315 -3.833 0.000126 ***
temp013 -0.0023532 0.0009683 -2.430 0.015087 *
rh13 0.0058769 0.0009909 5.931 3.01e-09 ***
rh013 -0.0028568 0.0006070 -4.706 2.52e-06 ***
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Correlation of Fixed Effects:
(Intr) pm.lg0 pm.lg1 pm.lg2 pm.lg3 pm.lg4 pm.lg5 temp13 tmp013 rh13
pm.lag0 -0.025
pm.lag1 -0.032 -0.154
pm.lag2 -0.021 0.044 -0.179
pm.lag3 0.002 0.003 0.033 -0.176
pm.lag4 0.016 0.102 -0.016 0.041 -0.176
pm.lag5 0.008 0.027 0.090 -0.002 0.040 -0.186
temp13 -0.316 0.026 0.027 0.004 -0.019 -0.055 -0.035
temp013 0.030 -0.015 0.051 0.015 -0.015 0.002 -0.069 -0.205
rh13 -0.350 0.043 0.078 0.056 -0.012 -0.042 -0.030 0.430 0.055
rh013 0.193 -0.008 -0.021 0.011 0.030 0.101 -0.028 -0.278 0.025 -0.524
我已经在这里为 p-value 列留了一个空间并为它输入了一个 colname,所以这个代码示例是不可操作的:
mixed.results <- mod
cbind(names(fixef(mod)),as.numeric(fixef(mod)),sqrt(diag(vcov(mod))), ???? )
mixed.results
colnames(mixed.results) <- c("Pred", "Coef", "St. Error", "Pr(>|z|)")
mixed.results
write.csv(mixed.results, file="mixedmod1.csv")
谢谢!
这只是coef(summary(model))
,我相信:
gm1 <- glmer(cbind(incidence, size - incidence) ~ period + (1 | herd),
data = cbpp, family = binomial)
cc <- coef(summary(gm1))
str(cc)
# num [1:4, 1:4] -1.376 -1.058 -1.196 -1.638 0.205 ...
# - attr(*, "dimnames")=List of 2
# ..$ : chr [1:4] "(Intercept)" "period2" "period3" "period4"
# ..$ : chr [1:4] "Estimate" "Std. Error" "z value" "Pr(>|z|)"
cc[,4] ## or cc[,"Pr(>|z)"] to be more explicit
# (Intercept) period2 period3 period4
#1.907080e-11 1.996120e-41 4.634385e-43 4.657952e-47
我使用了lme4
的开发版本,但我认为这已经工作了一段时间。
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