Last updated on 2025-12-28 03:51:55 CET.
| Package | ERROR | NOTE | OK |
|---|---|---|---|
| DeclareDesign | 1 | 12 | |
| randomizr | 10 | 3 | |
| ri2 | 13 | ||
| vayr | 13 |
Current CRAN status: ERROR: 1, OK: 12
Version: 1.1.0
Check: examples
Result: ERROR
Running examples in 'DeclareDesign-Ex.R' failed
The error most likely occurred in:
> ### Name: declare_estimator
> ### Title: Declare estimator
> ### Aliases: declare_estimator declare_estimators label_estimator
> ### method_handler
>
> ### ** Examples
>
>
> # Setup for examples
> design <-
+ declare_model(
+ N = 500,
+ gender = rbinom(N, 1, 0.5),
+ U = rnorm(N, sd = 0.25),
+ potential_outcomes(Y ~ rbinom(
+ N, 1, prob = pnorm(0.2 * Z + 0.2 * gender + 0.1 * Z * gender + U)
+ ))
+ ) +
+ declare_inquiry(ATE = mean(Y_Z_1 - Y_Z_0)) +
+ declare_sampling(S = complete_rs(N = N, n = 200)) +
+ declare_assignment(Z = complete_ra(N = N, m = 100)) +
+ declare_measurement(Y = reveal_outcomes(Y ~ Z))
>
> run_design(design)
inquiry estimand
1 ATE 0.138
>
> # default estimator is lm_robust with tidy summary
> design_0 <-
+ design +
+ declare_estimator(Y ~ Z, inquiry = "ATE")
>
> run_design(design_0)
inquiry estimand estimator term estimate std.error statistic p.value
1 ATE 0.082 estimator Z 0.01 0.07025926 0.14233 0.8869641
conf.low conf.high df outcome
1 -0.1285525 0.1485525 198 Y
>
> # Linear regression using lm_robust and tidy summary
> design_1 <-
+ design +
+ declare_estimator(
+ formula = Y ~ Z,
+ .method = lm_robust,
+ .summary = tidy,
+ term = "Z",
+ inquiry = "ATE",
+ label = "lm_no_controls"
+ )
>
> run_design(design_1)
inquiry estimand term estimator estimate std.error statistic p.value
1 ATE 0.106 Z lm_no_controls 0.01 0.06842381 0.146148 0.8839533
conf.low conf.high df outcome
1 -0.124933 0.144933 198 Y
>
> # Use glance summary function to view model fit statistics
> design_2 <-
+ design +
+ declare_estimator(.method = lm_robust,
+ formula = Y ~ Z,
+ .summary = glance)
>
> run_design(design_2)
inquiry estimand estimator r.squared adj.r.squared statistic p.value
1 ATE 0.062 estimator 0.00490049 -0.0001252651 0.9750754 0.3246228
df.residual nobs se_type
1 198 200 HC2
>
> # Custom answer strategies
> # A custom estimator should take data as an argument and return a data.frame
> # with columns such as "estimate", "std.error", "p.value", "conf.low", "conf.high"
> my_estimator <- function(data) {
+ data.frame(estimate = mean(data$Y))
+ }
>
> # Add a custom estimator to the design, wrapping it in `label_estimator()`
> # in order to pass label and inquiry arguments
>
> design_3 <-
+ design +
+ declare_inquiry(Y_bar = mean(Y)) +
+ declare_estimator(handler = label_estimator(my_estimator),
+ label = "mean",
+ inquiry = "Y_bar")
>
> run_design(design_3)
inquiry estimand estimator estimate
1 Y_bar 0.570 mean 0.57
2 ATE 0.136 <NA> NA
>
> # Use `term` to select particular coefficients
> design_4 <-
+ design +
+ declare_inquiry(difference_in_cates = mean(Y_Z_1[gender == 1] - Y_Z_0[gender == 1]) -
+ mean(Y_Z_1[gender == 0] - Y_Z_0[gender == 0])) +
+ declare_estimator(Y ~ Z * gender,
+ term = "Z:gender",
+ inquiry = "difference_in_cates",
+ .method = lm_robust)
>
> run_design(design_4)
inquiry estimand term estimator estimate std.error
1 difference_in_cates 0.1443609 Z:gender estimator 0.1966622 0.1381796
2 ATE 0.1180000 <NA> <NA> NA NA
statistic p.value conf.low conf.high df outcome
1 1.423236 0.1562576 -0.07584754 0.469172 196 Y
2 NA NA NA NA NA <NA>
>
> if(require("broom")) {
+
+ # Use glm from base R
+ design_5 <-
+ design +
+ declare_estimator(Y ~ Z + gender,
+ family = "gaussian",
+ inquiry = "ATE",
+ .method = glm)
+
+ run_design(design_5)
+
+ # If we use logit, we'll need to estimate the average marginal effect with
+ # marginaleffects::avg_slopes. We wrap this up in a function we'll pass to
+ # .summary.
+
+ if(require("marginaleffects")) {
+
+ library(marginaleffects) # for predictions
+ library(broom) # for tidy
+
+ tidy_avg_slopes <- function(x) {
+ tidy(avg_slopes(x))
+ }
+
+ design_6 <-
+ design +
+ declare_estimator(
+ Y ~ Z + gender,
+ .method = glm,
+ family = binomial("logit"),
+ .summary = tidy_avg_slopes,
+ term = "Z"
+ )
+
+ run_design(design_6)
+
+ # Multiple estimators for one inquiry
+
+ design_7 <-
+ design +
+ declare_estimator(Y ~ Z,
+ .method = lm_robust,
+ inquiry = "ATE",
+ label = "OLS") +
+ declare_estimator(
+ Y ~ Z + gender,
+ .method = glm,
+ family = binomial("logit"),
+ .summary = tidy_avg_slopes,
+ inquiry = "ATE",
+ term = "Z",
+ label = "logit"
+ )
+
+ run_design(design_7)
+
+ }
+
+ }
Loading required package: broom
Loading required package: marginaleffects
Error: Error in step 6 (estimator):
Error in `[.data.table`(out, , `:=`(tmp_idx, seq_len(.N)), by = tmp): attempt access index 11/11 in VECTOR_ELT
Execution halted
Flavor: r-devel-windows-x86_64
Current CRAN status: NOTE: 10, OK: 3
Version: 1.0.0
Check: compiled code
Result: NOTE
File ‘randomizr/libs/randomizr.so’:
Found non-API call to R: ‘SETLENGTH’
Compiled code should not call non-API entry points in R.
See ‘Writing portable packages’ in the ‘Writing R Extensions’ manual,
and section ‘Moving into C API compliance’ for issues with the use of
non-API entry points.
Flavors: r-devel-linux-x86_64-debian-clang, r-devel-linux-x86_64-debian-gcc, r-devel-linux-x86_64-fedora-clang, r-devel-linux-x86_64-fedora-gcc, r-patched-linux-x86_64, r-release-linux-x86_64, r-release-macos-arm64, r-release-macos-x86_64
Version: 1.0.0
Check: compiled code
Result: NOTE
File 'randomizr/libs/x64/randomizr.dll':
Found non-API call to R: 'SETLENGTH'
Compiled code should not call non-API entry points in R.
See 'Writing portable packages' in the 'Writing R Extensions' manual,
and section 'Moving into C API compliance' for issues with the use of
non-API entry points.
Flavors: r-devel-windows-x86_64, r-release-windows-x86_64
Current CRAN status: OK: 13
Current CRAN status: OK: 13
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