R: A Declarative Interface for Statistical Inference

# A Declarative Interface for Statistical Inference

## Documentation for package ‘statim’ version 0.1.0

- DESCRIPTION file
- User guides, package vignettes and other documentation
- Package NEWS
- Package README

## Help Pages

%<-% | Apply a method_tidy to a making_tidy target
%by% | Compare a variable by group
add-stat-define | Add or remove stat_define implementations on a test or model function
add-variant | Add or remove variant implementations on a test or model function
add_stat_define | Add or remove stat_define implementations on a test or model function
add_variant | Add or remove variant implementations on a test or model function
agendas | Collect implementations for a statistical procedure
anova | ANOVA table for linear model comparisons
anova-mod | ANOVA table for linear model comparisons
auto_gauge | Automatically gauge effect size from a statistical result
auto_predict | Automatically predict from a statistical result
auto_tidy | Automatically tidy a statistical result
baseline | Declare the canonical implementation of a test or model
check_param_nodes | Validate hypothesis parameter references against a model's declared variables
check_x_and_given | Validate hypothesis parameter references against a model's declared variables
claim-vars-validators | Validate hypothesis parameter references against a model's declared variables
claim_contrast_coefs | Extract contrast coefficients from a null claim
claim_scalar | Extract a scalar hypothesis value from a null claim
class_corr_two | Structured result container for two-sample t-tests
class_glm_object | Structured result container for GLM fits
class_lm_object | Structured result container for linear model fits
class_p_test | Structured result container for proportion tests
class_stat_infer | Base class for all statistical result objects
class_ttest_one | Structured result container for one-sample t-tests
class_ttest_pairwise | Structured result container for pairwise t-tests
class_ttest_two | Structured result container for two-sample t-tests
class_var_inform | Output class for Variable Mapper metadata
conclude | Execute a lazy pipeline
COR_TEST | Correlation Test
define_model | Define a layout supplied by a Variable Mapper
display | Display individual results
gauge | Effect size for a concluded statistical result
GLM | Generalized linear model
HTEST_FN | Build a hypothesis test function
inlines | Inline multiple expressions in a Variable Mapper
layout-define-base | Define a layout supplied by a Variable Mapper
LINEAR_REG | Linear regression
making_gauge | Declare a gauge method for a stat and model type
making_predict | Declare a predict method for a stat and model type
making_tidy | Declare tidy methods for a stat and model type
map_claim | Build a claim parser from named resolver functions
method_gauge | Declare gauge methods for a stat result
method_predict | Declare predict methods for a stat result
method_tidy | Declare tidy methods for a stat result
model-processor | Model evaluator
MODEL_FN | Build a model inference function
model_infer_define | Define a statistical procedure implementation
model_processor | Model evaluator
modifying-assignment | Apply a method_tidy to a making_tidy target
MU | Mean of a variable, optionally conditioned on a subgroup
null-hyp | State a null hypothesis in the pipeline
on | Specify variables for independent testing
pairwise | Define all pairwise variable combinations
param_obj | Base class for population parameters
PI | Proportion of a variable, optionally conditioned on a subgroup
predict | Predict from a concluded statistical result
prepare | Prepare a lazy inference pipeline
prepare-model | Lazily prepare a model inference
prepare-test | Lazily prepare a single test
prepare_model | Lazily prepare a model inference
prepare_test | Lazily prepare a single test
prop | Define a proportion test model
purge_stat_defines | Purge all package-scoped stat_define registrations for a package
P_TEST | Proportion Test
rel | Describe the relationship between two variables
remove_stat_define | Add or remove stat_define implementations on a test or model function
remove_variant | Add or remove variant implementations on a test or model function
RHO | Population correlation between two variables
stat-infer-definer | Define a statistical procedure implementation
state_null | State a null hypothesis in the pipeline
STAT_CONSTRUCTOR | Main foundation for inferential statistics
stat_define | Define a statistical procedure implementation
test_define | Define a statistical procedure implementation
tidy | Tidy a concluded statistical result
T_TEST | T-Test
validate_claim_vars | Validate hypothesis parameter references against a model's declared variables
validate_one_param_node | Validate hypothesis parameter references against a model's declared variables
variant | Declare an alternative implementation of a test or model
var_id | Base class for Variable Mapper objects
var_id_info | Extract metadata from a Variable Mapper
via | Recalibrate the method variant
write_models | Write multiple model definitions from a data frame
x_by | Compare a variable by group