KK Hurdle Poisson IVWC Inference for Count Responses

Inverse-variance weighted combined inference for count responses under a KK matching-on-the-fly design. The matched-pair component is fit with a hurdle-Poisson mixed model using pair random intercepts, and the reservoir component is fit with an ordinary Poisson log-link regression. The reported treatment effect is on the log-rate scale.

Super class

Inference -> InferenceCountKKHurdlePoissonIVWC

Methods

Public methods

• InferenceCountKKHurdlePoissonIVWC$set_custom_randomization_statistic_function()

• InferenceCountKKHurdlePoissonIVWC$set_custom_randomization_statistic_cpp()

• InferenceCountKKHurdlePoissonIVWC$approximate_randomization_distribution_beta_hat_T()

• InferenceCountKKHurdlePoissonIVWC$supports_rand_pval_for_incidence()

• InferenceCountKKHurdlePoissonIVWC$compute_rand_two_sided_pval()

• InferenceCountKKHurdlePoissonIVWC$clone()

+ inherited public methods from Inference

• Inference$capabilities()
• Inference$compute_asymp_confidence_interval()
• Inference$compute_asymp_two_sided_pval()
• Inference$compute_estimate()
• Inference$compute_exact_confidence_interval()
• Inference$compute_exact_two_sided_pval_for_treatment_effect()
• Inference$duplicate()
• Inference$get_analysis_data()
• Inference$get_covariates()
• Inference$get_design_object()
• Inference$get_model_formula()
• Inference$get_nonestimable_reason()
• Inference$get_nonestimable_stage()
• Inference$get_optimization_alg()
• Inference$get_response()
• Inference$get_response_type()
• Inference$get_treatment()
• Inference$initialize()
• Inference$is_nonestimable()
• Inference$set_optimization_alg()
• Inference$set_seed()
• Inference$supports()

---

InferenceCountKKHurdlePoissonIVWC$set_custom_randomization_statistic_function()

Usage

InferenceCountKKHurdlePoissonIVWC$set_custom_randomization_statistic_function(
  custom_randomization_statistic_function
)

---

InferenceCountKKHurdlePoissonIVWC$set_custom_randomization_statistic_cpp()

Usage

InferenceCountKKHurdlePoissonIVWC$set_custom_randomization_statistic_cpp(fn)

---

InferenceCountKKHurdlePoissonIVWC$approximate_randomization_distribution_beta_hat_T()

Usage

InferenceCountKKHurdlePoissonIVWC$approximate_randomization_distribution_beta_hat_T(
  r = 501,
  delta = 0,
  transform_responses = "none",
  show_progress = TRUE,
  permutations = NULL,
  debug = FALSE,
  zero_one_logit_clamp = .Machine$double.eps
)

---

InferenceCountKKHurdlePoissonIVWC$supports_rand_pval_for_incidence()

Usage

InferenceCountKKHurdlePoissonIVWC$supports_rand_pval_for_incidence()

---

InferenceCountKKHurdlePoissonIVWC$compute_rand_two_sided_pval()

Usage

InferenceCountKKHurdlePoissonIVWC$compute_rand_two_sided_pval(
  r = 501,
  delta = 0,
  transform_responses = "none",
  na.rm = TRUE,
  show_progress = TRUE,
  permutations = NULL,
  zero_one_logit_clamp = .Machine$double.eps
)

---

InferenceCountKKHurdlePoissonIVWC$clone()

The objects of this class are cloneable with this method.

Usage

InferenceCountKKHurdlePoissonIVWC$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.