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Edits round 1 #12

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da7b11a
rm .DS_Store
tgerke May 28, 2023
a4986fd
light edits and linting
tgerke May 28, 2023
8176a5f
wrangle duplicate cases in a single call
tgerke May 28, 2023
92dea8a
lint, minor edits
tgerke May 28, 2023
720df64
big refactor; move most switch and if/else to explicit if blocks
tgerke May 29, 2023
02656d3
fixes #17
tgerke Jun 2, 2023
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18 changes: 10 additions & 8 deletions R/caseduplicate.R
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Original file line number Diff line number Diff line change
Expand Up @@ -7,14 +7,16 @@
# (Miettinen/Schouten approach to directly estimating relative risks)
estimate_duplicate <- function(formula, data, ...) {
yvar <- as.character(all.vars(formula)[1])
data <- data %>%
dplyr::mutate(.clusterid = dplyr::row_number())
data <- dplyr::bind_rows(data,
data %>%
dplyr::rename(outc = dplyr::one_of(!!yvar)) %>%
dplyr::filter(.data$outc == 1) %>%
dplyr::mutate(outc = 0) %>%
dplyr::rename(!!yvar := "outc"))

data <- data |>
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see earlier comment about base R pipe

dplyr::mutate(.clusterid = dplyr::row_number()) |>
dplyr::rename(outc = dplyr::one_of(!!yvar)) |>
tidyr::uncount(outc + 1) |>
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The see the elegance in this approach! However, in the spirit of my comment in #10, it would be nice not to rely on tidyverse functions down the road. Let us focus on testing and bug fixes for now.

dplyr::group_by(.clusterid) |>
dplyr::mutate(outc = floor(outc / dplyr::row_number())) |>
dplyr::ungroup() |>
dplyr::rename(!!yvar := "outc")

fit <- eval(substitute(stats::glm(formula = formula,
family = binomial(link = "logit"),
data = data)))
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