在R中使用CMAverse，当我运行相同的模型两次时，我似乎不能得到相同的结果。示例代码：
# Load packages and set seed.
library(CMAverse)
library(tidyverse)
library(magrittr)
library(janitor)
set.seed(1)
# Simulate data containing a continuous baseline confounder C1, a binary baseline confounder C2, a binary exposure A, a binary mediator M and a binary outcome Y.
expit <- function(x) exp(x)/(1+exp(x))
n <- 10000
C1 <- rnorm(n, mean = 1, sd = 0.1)
C2 <- rbinom(n, 1, 0.6)
A <- rbinom(n, 1, expit(0.2 + 0.5*C1 + 0.1*C2))
M <- rbinom(n, 1, expit(1 + 2*A + 1.5*C1 + 0.8*C2))
Y <- rbinom(n, 1, expit(-3 - 0.4*A - 1.2*M + 0.5*A*M + 0.3*C1 - 0.6*C2))
data <- data.frame(A, M, Y, C1, C2)
# Run causal mediation analysis.
model <- cmest(data = data, model = "rb", outcome = "Y", exposure = "A",
mediator = "M", basec = c("C1", "C2"), EMint = TRUE,
mreg = list("logistic"), yreg = "logistic",
astar = 0, a = 1, mval = list(1), yval=1,
estimation = "imputation", inference = "bootstrap", nboot = 10)
# Get the summary of the model.
summary <- model %>% summary()
summary$summarydf %>% clean_names() %>% mutate_at(vars(estimate, x95_percent_cil, x95_percent_ciu), ~format(round(., digits=2), nsmall=2, trim=TRUE)) %>% mutate(estimate=paste0(estimate, " (", x95_percent_cil, "-", x95_percent_ciu, ")")) %>% select(-x95_percent_cil, -x95_percent_ciu) %>% mutate(p_val=format(round(p_val, digits=3), nsmall=3))
# The pure natural direct effect is 1.42 (1.27-1.87) and the pure natural indirect effect is 0.92 (0.89-0.98).
# Rerun the causal mediation analysis.
model <- cmest(data = data, model = "rb", outcome = "Y", exposure = "A",
mediator = "M", basec = c("C1", "C2"), EMint = TRUE,
mreg = list("logistic"), yreg = "logistic",
astar = 0, a = 1, mval = list(1), yval=1,
estimation = "imputation", inference = "bootstrap", nboot = 10)
# Get the summary of the model.
summary <- model %>% summary()
summary$summarydf %>% clean_names() %>% mutate_at(vars(estimate, x95_percent_cil, x95_percent_ciu), ~format(round(., digits=2), nsmall=2, trim=TRUE)) %>% mutate(estimate=paste0(estimate, " (", x95_percent_cil, "-", x95_percent_ciu, ")")) %>% select(-x95_percent_cil, -x95_percent_ciu) %>% mutate(p_val=format(round(p_val, digits=3), nsmall=3))
# The pure natural direct effect is 1.43 (1.08-1.75) and the pure natural indirect effect is 0.91 (0.85-0.99).如何让R在重新运行相同的模型时给予相同的结果？
2条答案
按热度按时间uidvcgyl1#
首先运行这个“set.seed（123）”，然后运行模型，你会得到相同的结果
lyr7nygr2#
我没有运行你的整个脚本，因为
CMAverse不适用于我运行的R版本，但我猜你没有在每次运行代码时都运行set.seed()？如果你希望每次调用rnorm()时都有相同的值，你必须每次运行set.seed()。例如：将产生具有不同值的向量，而：
我会一遍又一遍地重复相同的向量。如果这不能解决你的问题，让我知道，我会进一步探讨你的问题。