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我正在尝试使用 RglmmTMB函数来改变零膨胀泊松模型的固定和随机效应。我想将修改后的固定效果输入到powerSim函数中。这是数据：

sample <- as.data.frame(cbind(1:50, (rep(1:10, each = 5))))

#randomize interventions by clinic
ru1 <- cbind(rbinom(10, 1, 0.5), 1:10)
ru2 <- cbind(rbinom(10, 1, 0.5), 1:10)

#merge randomization id with original sample 
sample <- merge(sample, ru1, by = "V2") %>% merge(ru2)

#add days 
sample <- as.data.frame(cbind(sample, scale(rep(-546:546, each = 50))))

#order by clinic and prescriber
sample <- sample[order(sample$V2, sample$V1.x),]

#simulate ZIP distribution for days supply
set.seed(789)
sample <- cbind(sample, ifelse(rbinom(54650, 1, p = 0.5) > 0, 0, rpois(54650, 5)))

#rename variables
sample <- rename(sample, pres = V1.x, clinic = V2, aj = V1.y, def = V1, 
                 days = `scale(rep(-546:546, each = 50))`, 
                 dayssply = `ifelse(rbinom(54650, 1, p = 0.5) > 0, 0, rpois(54650, 5))`)

#days truncated
sample$days_ <- ifelse(0 > sample$days, 0, sample$days)

#model 
m1 <- glmmTMB(dayssply ~ aj*days_ + (1|clinic/pres), zi = ~ aj*days_, 
        data = sample, family = poisson)

经过大量的试验和错误，我终于想出了如何使用 fixef 函数指定条件固定效果：

fixef(m1)$cond [["aj"]]

但是，当我尝试将其更改为功率分析所需的固定效应时，我收到“cond 不是固定效应的名称”的错误。不确定这是否是与语法相关的问题，或者 fixef 是否不适用于零膨胀模型。

我还想使用 VarCorr 更改随机效应的方差。

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