我正在尝试使用 dplyr::pivot_longer 转换为更长的格式，但似乎无法让它执行我想要的操作。我可以使用 reshape::melt 进行管理，但我也希望能够使用pivot_longer 实现相同的目的。
我尝试重新格式化的数据是 mtcars 数据集的相关矩阵：
# Load packages
library(reshape2)
library(dplyr)
# Get the correlation matrix
mydata <- mtcars[, c(1,3,4,5,6,7)]
cormat <- round(cor(mydata),2)
head(cormat)
mpg disp hp drat wt qsec
mpg 1.00 -0.85 -0.78 0.68 -0.87 0.42
disp -0.85 1.00 0.79 -0.71 0.89 -0.43
hp -0.78 0.79 1.00 -0.45 0.66 -0.71
drat 0.68 -0.71 -0.45 1.00 -0.71 0.09
wt -0.87 0.89 0.66 -0.71 1.00 -0.17
qsec 0.42 -0.43 -0.71 0.09 -0.17 1.00
然后，我只想过滤掉矩阵的上三角形；
#Get upper triangle of …我正在尝试使用包pivot_longer中的函数dplyr将我的数据转换为长格式。当前的广泛数据涉及 3 次重复测量患者的年龄、收缩压、是否使用降压药物 (med_hypt) 以及时间不变的“性别”变量。
示例数据和我尝试过的：
library(tidyverse)
library(dplyr)
library(magrittr)
wide_data <- structure(list(id = c(12002, 17001, 17002, 42001, 66001, 82002, 166002, 177001, 177002, 240001),
sex = structure(c(2L, 1L, 2L, 1L, 1L, 1L, 2L, 2L, 1L, 1L),
.Label = c("men", "women"), class = "factor"),
time1_age = c(71.2, 67.9, 66.5, 57.7, 57.1, 60.9, 80.9, 59.7, 58.2, 66.6),
time1_systolicBP = c(102, 152, NA_real_, 170, 151, 135, 162, 133, 131, 117),
time1_med_hypt = c(0, 0, 0, 0, 0, 0, 0, 0, …我对连续结果进行了重复测量，如下所示：
library(magrittr)
library(ggplot2)
library(nlme)
mydata <- structure(list(ID = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L,
3L, 3L, 3L, 3L, 3L, 4L, 4L, 5L, 5L, 5L, 6L, 6L, 6L, 6L, 6L, 7L,
7L, 7L, 7L, 7L, 8L, 8L, 9L, 9L, 10L, 10L, 11L, 11L, 11L, 11L,
12L, 12L, 13L, 13L, 14L, 14L, 14L, 14L, 14L, 15L, 15L, 16L, 16L,
17L, 17L, 17L, 17L, 17L, 18L, 18L, 19L, 19L, 20L, 20L, 21L, 21L,
22L, 22L, 22L, 22L, 22L, 23L, 23L, 24L, …我有 3 名患者的重复测量（4 或 5 次）的长格式数据：
library(dplyr)
library(magrittr)
questiondata <- structure(list(ID = c(2, 2, 2, 2, 3, 3, 3, 3, 3, 4, 4, 4, 4,
4), time = c("time1", "time2", "time3", "time4", "time1", "time2",
"time3", "time4", "time5", "time1", "time2", "time3", "time4",
"time5"), drug_use = structure(c(NA, 1L, NA, NA, NA, 2L, NA,
NA, NA, NA, 1L, NA, NA, NA), .Label = c("no", "yes"), class = "factor")), row.names = c(NA,
-14L), class = c("tbl_df", "tbl", "data.frame"))
# Corresponding to the following tibble: …为了显示我运行的回归结果，我有一个包含估计值和相应置信区间的小标题：
\nlibrary(tidyverse)\nlibrary(magrittr\n\nmydata <- structure(list(term = structure(c(1L, 3L, 4L), .Label = c("Intercept", \n"Follow-up time (years)", "Age (years)", "Sex (male)", "Never smoker (reference)", \n"Current smoker", "Former smoker", "Obesity (=30 kg/m\xc2\xb2)", "BMI (kg/m\xc2\xb2)", \n"Diabetes", "Glucose (mmol/L)", "Glucose lowering medication use", \n"Hypertension", "Systolic blood pressure (mmHg)", "Diastolic blood pressure (mmHg)", \n"Antihypertensive medication use", "Hypercholesterolemia", "LDL cholesterol (mmol/L)", \n"Lipid lowering medication use", "Chronic kidney disease (mL/min/1.73m\xc2\xb2)", \n"=90 (reference)", "60-89", "=60"), class = c("ordered", "factor"\n)), estimate = c(518.38, 0.98, 1.07), conf_low = c(178.74, 0.93, \n0.96), …