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new tibble export
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@@ -54,26 +54,34 @@ if (require("dplyr")) {
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# episodes based on any (combination of) grouping variables:
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df \%>\%
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mutate(condition = sample(x = c("A", "B", "C"),
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size = 2000,
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size = 200,
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replace = TRUE)) \%>\%
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group_by(condition) \%>\%
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mutate(new_episode = is_new_episode(date, 365)) \%>\%
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select(patient_id, date, condition, new_episode)
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select(patient, date, condition, new_episode)
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}
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if (require("dplyr")) {
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df \%>\%
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group_by(hospital_id, patient_id) \%>\%
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group_by(ward, patient) \%>\%
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transmute(date,
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patient_id,
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patient,
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new_index = get_episode(date, 60),
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new_logical = is_new_episode(date, 60))
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}
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if (require("dplyr")) {
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df \%>\%
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group_by(hospital_id) \%>\%
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summarise(n_patients = n_distinct(patient_id),
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group_by(ward) \%>\%
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summarise(n_patients = n_distinct(patient),
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n_episodes_365 = sum(is_new_episode(date, episode_days = 365)),
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n_episodes_60 = sum(is_new_episode(date, episode_days = 60)),
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n_episodes_30 = sum(is_new_episode(date, episode_days = 30)))
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}
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if (require("dplyr")) {
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# grouping on patients and microorganisms leads to the same
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# results as first_isolate() when using 'episode-based':
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@@ -82,16 +90,19 @@ if (require("dplyr")) {
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method = "episode-based")
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y <- df \%>\%
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group_by(patient_id, mo) \%>\%
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group_by(patient, mo) \%>\%
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filter(is_new_episode(date, 365)) \%>\%
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ungroup()
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identical(x, y)
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}
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if (require("dplyr")) {
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# but is_new_episode() has a lot more flexibility than first_isolate(),
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# since you can now group on anything that seems relevant:
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df \%>\%
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group_by(patient_id, mo, hospital_id, ward_icu) \%>\%
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group_by(patient, mo, ward) \%>\%
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mutate(flag_episode = is_new_episode(date, 365)) \%>\%
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select(group_vars(.), flag_episode)
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}
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