Data used in weight model fitting
Usage
weight_model_data_indices(
object,
type = c("switch", "censor"),
model,
set_col = NULL
)Arguments
- object
A trial_sequence object
- type
Select a censoring or switching model
- model
The model name
- set_col
A character string to specifying a new column to contain indicators for observations used in fitting this model.
Examples
trial_pp <- trial_sequence("PP") |>
set_data(data_censored) |>
set_switch_weight_model(
numerator = ~age,
denominator = ~ age + x1 + x3,
model_fitter = stats_glm_logit(tempdir())
) |>
calculate_weights()
ipw_data(trial_pp)
#> Key: <id>
#> Indices: <am_1>, <treatment>
#> id period treatment x1 x2 x3 x4 age age_s
#> <int> <int> <num> <num> <num> <int> <num> <num> <num>
#> 1: 1 0 1 1 1.146148362 0 0.7342030 36 0.08333333
#> 2: 1 1 1 1 0.002200337 0 0.7342030 37 0.16666667
#> 3: 1 2 1 0 -0.481762418 0 0.7342030 38 0.25000000
#> 4: 1 3 1 0 0.007872396 0 0.7342030 39 0.33333333
#> 5: 1 4 1 1 0.216053715 0 0.7342030 40 0.41666667
#> ---
#> 317: 98 2 1 0 -0.735240928 0 0.3174175 66 2.58333333
#> 318: 98 3 0 0 -0.425345479 0 0.3174175 67 2.66666667
#> 319: 99 0 1 1 -0.346377841 1 0.5752681 65 2.50000000
#> 320: 99 1 1 0 -1.106480738 1 0.5752681 66 2.58333333
#> 321: 99 2 0 0 1.650478074 1 0.5752681 67 2.66666667
#> outcome censored eligible time_of_event first am_1 cumA switch
#> <num> <int> <num> <num> <lgcl> <num> <num> <num>
#> 1: 0 0 1 9999 TRUE 0 1 0
#> 2: 0 0 0 9999 FALSE 1 2 0
#> 3: 0 0 0 9999 FALSE 1 3 0
#> 4: 0 0 0 9999 FALSE 1 4 0
#> 5: 0 0 0 9999 FALSE 1 5 0
#> ---
#> 317: 0 0 0 14 FALSE 1 3 0
#> 318: 0 0 0 14 FALSE 1 3 1
#> 319: 0 0 1 7 TRUE 0 1 0
#> 320: 0 0 0 7 FALSE 1 2 0
#> 321: 0 0 0 7 FALSE 1 2 1
#> regime_start time_on_regime eligible0 eligible1 wt p_n
#> <int> <num> <num> <num> <num> <num>
#> 1: 0 0 1 0 0.7964844 0.4706283
#> 2: 0 1 0 1 0.9274210 0.7174218
#> 3: 0 2 0 1 1.0750073 0.7126312
#> 4: 0 3 0 1 1.0761263 0.7077924
#> 5: 0 4 0 1 0.9234340 0.7029062
#> ---
#> 317: 0 2 0 1 1.1082753 0.5621482
#> 318: 3 3 0 1 0.8898716 0.5563530
#> 319: 0 0 1 0 0.8816779 0.2512156
#> 320: 0 1 0 1 1.0034178 0.5621482
#> 321: 2 2 0 1 0.9959067 0.5563530
#> p_d wtS
#> <num> <num>
#> 1: 0.5908820 0.7964844
#> 2: 0.7735665 0.9274210
#> 3: 0.6629082 1.0750073
#> 4: 0.6577225 1.0761263
#> 5: 0.7611872 0.9234340
#> ---
#> 317: 0.5072279 1.1082753
#> 318: 0.5014484 0.8898716
#> 319: 0.2849290 0.8816779
#> 320: 0.5602335 1.0034178
#> 321: 0.5545296 0.9959067
show_weight_models(trial_pp)
#> Weight Models for Informative Censoring
#> ---------------------------------------
#>
#> Weight Models for Treatment Switching
#> -------------------------------------
#>
#> [[n1]]
#> Model: P(treatment = 1 | previous treatment = 1) for numerator
#>
#> term estimate std.error statistic p.value
#> (Intercept) 1.80162178 0.77463133 2.325780 0.02003031
#> age -0.02351116 0.01691961 -1.389581 0.16465623
#>
#> null.deviance df.null logLik AIC BIC deviance df.residual nobs
#> 188.829 150 -93.43779 190.8756 196.9101 186.8756 149 151
#>
#> path
#> /tmp/RtmpRXqWy2/model_172161d222ee.rds
#>
#> [[d1]]
#> Model: P(treatment = 1 | previous treatment = 1) for denominator
#>
#> term estimate std.error statistic p.value
#> (Intercept) 1.55485166 0.81706997 1.9029602 0.05704573
#> age -0.02312027 0.01696843 -1.3625460 0.17302562
#> x1 0.52915871 0.43594855 1.2138100 0.22482028
#> x3 0.21319587 0.35744378 0.5964459 0.55087740
#>
#> null.deviance df.null logLik AIC BIC deviance df.residual nobs
#> 188.829 150 -92.54787 193.0957 205.1649 185.0957 147 151
#>
#> path
#> /tmp/RtmpRXqWy2/model_17217a04d538.rds
#>
#> [[n0]]
#> Model: P(treatment = 1 | previous treatment = 0) for numerator
#>
#> term estimate std.error statistic p.value
#> (Intercept) 1.09212298 0.60582678 1.802698 0.07143559
#> age -0.03360404 0.01439482 -2.334453 0.01957201
#>
#> null.deviance df.null logLik AIC BIC deviance df.residual nobs
#> 232.2705 169 -113.2746 230.5492 236.8208 226.5492 168 170
#>
#> path
#> /tmp/RtmpRXqWy2/model_172168ee760f.rds
#>
#> [[d0]]
#> Model: P(treatment = 1 | previous treatment = 0) for denominator
#>
#> term estimate std.error statistic p.value
#> (Intercept) 1.03084683 0.63052714 1.6348969 0.10207067
#> age -0.03633255 0.01472576 -2.4672779 0.01361446
#> x1 0.64473751 0.32346837 1.9932011 0.04623943
#> x3 -0.23411026 0.32147930 -0.7282281 0.46647397
#>
#> null.deviance df.null logLik AIC BIC deviance df.residual nobs
#> 232.2705 169 -111.03 230.06 242.6032 222.06 166 170
#>
#> path
#> /tmp/RtmpRXqWy2/model_172130dacfe1.rds
#>
# get logical column for own processing
i <- weight_model_data_indices(trial_pp, "switch", "d0")
# set column in data
weight_model_data_indices(trial_pp, "switch", "d0", set_col = "sw_d0")
#> Key: <id>
#> Indices: <am_1>, <treatment>
#> id period treatment x1 x2 x3 x4 age age_s
#> <int> <int> <num> <num> <num> <int> <num> <num> <num>
#> 1: 1 0 1 1 1.146148362 0 0.7342030 36 0.08333333
#> 2: 1 1 1 1 0.002200337 0 0.7342030 37 0.16666667
#> 3: 1 2 1 0 -0.481762418 0 0.7342030 38 0.25000000
#> 4: 1 3 1 0 0.007872396 0 0.7342030 39 0.33333333
#> 5: 1 4 1 1 0.216053715 0 0.7342030 40 0.41666667
#> ---
#> 317: 98 2 1 0 -0.735240928 0 0.3174175 66 2.58333333
#> 318: 98 3 0 0 -0.425345479 0 0.3174175 67 2.66666667
#> 319: 99 0 1 1 -0.346377841 1 0.5752681 65 2.50000000
#> 320: 99 1 1 0 -1.106480738 1 0.5752681 66 2.58333333
#> 321: 99 2 0 0 1.650478074 1 0.5752681 67 2.66666667
#> outcome censored eligible time_of_event first am_1 cumA switch
#> <num> <int> <num> <num> <lgcl> <num> <num> <num>
#> 1: 0 0 1 9999 TRUE 0 1 0
#> 2: 0 0 0 9999 FALSE 1 2 0
#> 3: 0 0 0 9999 FALSE 1 3 0
#> 4: 0 0 0 9999 FALSE 1 4 0
#> 5: 0 0 0 9999 FALSE 1 5 0
#> ---
#> 317: 0 0 0 14 FALSE 1 3 0
#> 318: 0 0 0 14 FALSE 1 3 1
#> 319: 0 0 1 7 TRUE 0 1 0
#> 320: 0 0 0 7 FALSE 1 2 0
#> 321: 0 0 0 7 FALSE 1 2 1
#> regime_start time_on_regime eligible0 eligible1 wt p_n
#> <int> <num> <num> <num> <num> <num>
#> 1: 0 0 1 0 0.7964844 0.4706283
#> 2: 0 1 0 1 0.9274210 0.7174218
#> 3: 0 2 0 1 1.0750073 0.7126312
#> 4: 0 3 0 1 1.0761263 0.7077924
#> 5: 0 4 0 1 0.9234340 0.7029062
#> ---
#> 317: 0 2 0 1 1.1082753 0.5621482
#> 318: 3 3 0 1 0.8898716 0.5563530
#> 319: 0 0 1 0 0.8816779 0.2512156
#> 320: 0 1 0 1 1.0034178 0.5621482
#> 321: 2 2 0 1 0.9959067 0.5563530
#> p_d wtS sw_d0
#> <num> <num> <lgcl>
#> 1: 0.5908820 0.7964844 TRUE
#> 2: 0.7735665 0.9274210 FALSE
#> 3: 0.6629082 1.0750073 FALSE
#> 4: 0.6577225 1.0761263 FALSE
#> 5: 0.7611872 0.9234340 FALSE
#> ---
#> 317: 0.5072279 1.1082753 FALSE
#> 318: 0.5014484 0.8898716 FALSE
#> 319: 0.2849290 0.8816779 TRUE
#> 320: 0.5602335 1.0034178 FALSE
#> 321: 0.5545296 0.9959067 FALSE
weight_model_data_indices(trial_pp, "switch", "d1", set_col = "sw_d1")
#> Key: <id>
#> Indices: <am_1>, <treatment>
#> id period treatment x1 x2 x3 x4 age age_s
#> <int> <int> <num> <num> <num> <int> <num> <num> <num>
#> 1: 1 0 1 1 1.146148362 0 0.7342030 36 0.08333333
#> 2: 1 1 1 1 0.002200337 0 0.7342030 37 0.16666667
#> 3: 1 2 1 0 -0.481762418 0 0.7342030 38 0.25000000
#> 4: 1 3 1 0 0.007872396 0 0.7342030 39 0.33333333
#> 5: 1 4 1 1 0.216053715 0 0.7342030 40 0.41666667
#> ---
#> 317: 98 2 1 0 -0.735240928 0 0.3174175 66 2.58333333
#> 318: 98 3 0 0 -0.425345479 0 0.3174175 67 2.66666667
#> 319: 99 0 1 1 -0.346377841 1 0.5752681 65 2.50000000
#> 320: 99 1 1 0 -1.106480738 1 0.5752681 66 2.58333333
#> 321: 99 2 0 0 1.650478074 1 0.5752681 67 2.66666667
#> outcome censored eligible time_of_event first am_1 cumA switch
#> <num> <int> <num> <num> <lgcl> <num> <num> <num>
#> 1: 0 0 1 9999 TRUE 0 1 0
#> 2: 0 0 0 9999 FALSE 1 2 0
#> 3: 0 0 0 9999 FALSE 1 3 0
#> 4: 0 0 0 9999 FALSE 1 4 0
#> 5: 0 0 0 9999 FALSE 1 5 0
#> ---
#> 317: 0 0 0 14 FALSE 1 3 0
#> 318: 0 0 0 14 FALSE 1 3 1
#> 319: 0 0 1 7 TRUE 0 1 0
#> 320: 0 0 0 7 FALSE 1 2 0
#> 321: 0 0 0 7 FALSE 1 2 1
#> regime_start time_on_regime eligible0 eligible1 wt p_n
#> <int> <num> <num> <num> <num> <num>
#> 1: 0 0 1 0 0.7964844 0.4706283
#> 2: 0 1 0 1 0.9274210 0.7174218
#> 3: 0 2 0 1 1.0750073 0.7126312
#> 4: 0 3 0 1 1.0761263 0.7077924
#> 5: 0 4 0 1 0.9234340 0.7029062
#> ---
#> 317: 0 2 0 1 1.1082753 0.5621482
#> 318: 3 3 0 1 0.8898716 0.5563530
#> 319: 0 0 1 0 0.8816779 0.2512156
#> 320: 0 1 0 1 1.0034178 0.5621482
#> 321: 2 2 0 1 0.9959067 0.5563530
#> p_d wtS sw_d0 sw_d1
#> <num> <num> <lgcl> <lgcl>
#> 1: 0.5908820 0.7964844 TRUE FALSE
#> 2: 0.7735665 0.9274210 FALSE TRUE
#> 3: 0.6629082 1.0750073 FALSE TRUE
#> 4: 0.6577225 1.0761263 FALSE TRUE
#> 5: 0.7611872 0.9234340 FALSE TRUE
#> ---
#> 317: 0.5072279 1.1082753 FALSE TRUE
#> 318: 0.5014484 0.8898716 FALSE TRUE
#> 319: 0.2849290 0.8816779 TRUE FALSE
#> 320: 0.5602335 1.0034178 FALSE TRUE
#> 321: 0.5545296 0.9959067 FALSE TRUE
ipw_data(trial_pp)
#> Key: <id>
#> Indices: <am_1>, <treatment>
#> id period treatment x1 x2 x3 x4 age age_s
#> <int> <int> <num> <num> <num> <int> <num> <num> <num>
#> 1: 1 0 1 1 1.146148362 0 0.7342030 36 0.08333333
#> 2: 1 1 1 1 0.002200337 0 0.7342030 37 0.16666667
#> 3: 1 2 1 0 -0.481762418 0 0.7342030 38 0.25000000
#> 4: 1 3 1 0 0.007872396 0 0.7342030 39 0.33333333
#> 5: 1 4 1 1 0.216053715 0 0.7342030 40 0.41666667
#> ---
#> 317: 98 2 1 0 -0.735240928 0 0.3174175 66 2.58333333
#> 318: 98 3 0 0 -0.425345479 0 0.3174175 67 2.66666667
#> 319: 99 0 1 1 -0.346377841 1 0.5752681 65 2.50000000
#> 320: 99 1 1 0 -1.106480738 1 0.5752681 66 2.58333333
#> 321: 99 2 0 0 1.650478074 1 0.5752681 67 2.66666667
#> outcome censored eligible time_of_event first am_1 cumA switch
#> <num> <int> <num> <num> <lgcl> <num> <num> <num>
#> 1: 0 0 1 9999 TRUE 0 1 0
#> 2: 0 0 0 9999 FALSE 1 2 0
#> 3: 0 0 0 9999 FALSE 1 3 0
#> 4: 0 0 0 9999 FALSE 1 4 0
#> 5: 0 0 0 9999 FALSE 1 5 0
#> ---
#> 317: 0 0 0 14 FALSE 1 3 0
#> 318: 0 0 0 14 FALSE 1 3 1
#> 319: 0 0 1 7 TRUE 0 1 0
#> 320: 0 0 0 7 FALSE 1 2 0
#> 321: 0 0 0 7 FALSE 1 2 1
#> regime_start time_on_regime eligible0 eligible1 wt p_n
#> <int> <num> <num> <num> <num> <num>
#> 1: 0 0 1 0 0.7964844 0.4706283
#> 2: 0 1 0 1 0.9274210 0.7174218
#> 3: 0 2 0 1 1.0750073 0.7126312
#> 4: 0 3 0 1 1.0761263 0.7077924
#> 5: 0 4 0 1 0.9234340 0.7029062
#> ---
#> 317: 0 2 0 1 1.1082753 0.5621482
#> 318: 3 3 0 1 0.8898716 0.5563530
#> 319: 0 0 1 0 0.8816779 0.2512156
#> 320: 0 1 0 1 1.0034178 0.5621482
#> 321: 2 2 0 1 0.9959067 0.5563530
#> p_d wtS sw_d0 sw_d1
#> <num> <num> <lgcl> <lgcl>
#> 1: 0.5908820 0.7964844 TRUE FALSE
#> 2: 0.7735665 0.9274210 FALSE TRUE
#> 3: 0.6629082 1.0750073 FALSE TRUE
#> 4: 0.6577225 1.0761263 FALSE TRUE
#> 5: 0.7611872 0.9234340 FALSE TRUE
#> ---
#> 317: 0.5072279 1.1082753 FALSE TRUE
#> 318: 0.5014484 0.8898716 FALSE TRUE
#> 319: 0.2849290 0.8816779 TRUE FALSE
#> 320: 0.5602335 1.0034178 FALSE TRUE
#> 321: 0.5545296 0.9959067 FALSE TRUE