56 lines
1.8 KiB
R
56 lines
1.8 KiB
R
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ds <- readr::read_csv(here::here("/Volumes/Data/REDCap/DDV/talos_ddv.csv"))
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df_raw <- ds |>
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dplyr::filter(!pase_score_missings_0, !pase_score_missings_4) |>
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dplyr::transmute(
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id = dplyr::row_number(),
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pase_0 = pase_score_sum_0,
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pase_4 = pase_score_sum_4,
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pase_0_cut = as.numeric(stRoke::quantile_cut(
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x = pase_0,
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groups = 4,
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group.names = paste0(1:4)
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)),
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pase_6_cut = as.numeric(stRoke::quantile_cut(
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x = pase_4,
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y = pase_0,
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groups = 4,
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inc.outs = TRUE,
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group.names = paste0(1:4)
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)),
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pase_diff = pase_4 - pase_0,
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pase_diff_rel = pase_diff / pase_0,
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pase_0_rank = rank(pase_0, ties.method = "first"),
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pase_4_rank = rank(pase_4, ties.method = "first"),
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change = dplyr::case_when(
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pase_0_cut %in% 2:4 & pase_6_cut == 1 ~ "drop",
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pase_6_cut %in% 2:4 & pase_0_cut == 1 ~ "hop",
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pase_0_cut %in% 2:4 & pase_6_cut %in% 2:4 ~ "hh",
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pase_0_cut %in% 1 & pase_6_cut == 1 ~ "ll"
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),
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change_any = factor(dplyr::case_when(
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pase_6_cut > pase_0_cut ~ "hop",
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pase_6_cut < pase_0_cut ~ "drop",
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pase_0_cut %in% 2:4 & pase_6_cut %in% 2:4 ~ "hh",
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pase_0_cut %in% 1 & pase_6_cut == 1 ~ "ll"
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)),
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change_rel = factor(dplyr::case_when(
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pase_diff_rel > .5 ~ "hop",
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pase_diff_rel < -.5 ~ "drop",
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.default = "stat"
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))
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)
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df_raw |> skimr::skim()
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df_long <- df_raw |>
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dplyr::select(pase_0_rank, pase_4_rank, change_rel,id) |>
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tidyr::pivot_longer(dplyr::starts_with("pase_"), names_to = "time", values_to = "pase")
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df_long <- df_raw |>
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dplyr::select(pase_0, pase_4, change_rel,id) |>
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tidyr::pivot_longer(dplyr::starts_with("pase_"), names_to = "time", values_to = "pase")
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ggplot(df_long, aes(x = time, y = pase,group=id,colour = change_rel)) +
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geom_line()+
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facet_wrap(~change_rel)
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