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Merge pull request #39 from egouldo/respond-reviews
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Address major reviewer changes
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egouldo authored Jul 24, 2024
2 parents a697e6c + 916024c commit 9a12006
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4 changes: 2 additions & 2 deletions _freeze/index/execute-results/html.json

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1 change: 1 addition & 0 deletions _freeze/renv/library/R-4.4/aarch64-apple-darwin20/BH
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citHeader("To cite ManyEcoEvo in publications use:")

bibentry(
bibtype = "Article",
title = "ManyEcoEvo: Meta-analyse data from ManyAnalyst style studies",
author = c(person(given = "Elliot",
family = "Gould",
email = "elliot.gould@unimelb.edu.au",
role = c("aut", "cre"),
comment = c(ORCID = "https://orcid.org/0000-0002-6585-538X")),
person(given = "Hannah S.",
family = "Fraser",
role = "aut",
comment = c(ORCID = "https://orcid.org/0000-0003-2443-4463")),
person(given = "Shinichi",
family = "Nakagawa",
role = "aut",
comment = c(ORCID = "https://orcid.org/0000-0002-7765-5182")),
person(given = "Timothy H.",
family = "Parker",
role = "aut",
comment = c(ORCID = "https://orcid.org/0000-0003-2995-5284"))
),
journal = "TBC",
year = "2023",
#note = "R package version 1.3-4",
#url = "https://CRAN.R-project.org/package=boot",
#key = "boot-package"
)
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Package: ManyEcoEvo
Title: Meta-analyse data from 'Many-Analysts' style studies
Version: 1.5.0.9000
Authors@R: c(person(given = "Elliot", family = "Gould", email = "elliot.gould@unimelb.edu.au", role = c("aut", "cre"), comment = c(ORCID = "https://orcid.org/0000-0002-6585-538X")), person(given = "Hannah S.", family = "Fraser", role = "aut", comment = c(ORCID = "https://orcid.org/0000-0003-2443-4463")), person(given = "Shinichi", family = "Nakagawa", role = "aut", comment = c(ORCID = "https://orcid.org/0000-0002-7765-5182")), person(given = "Timothy H.", family = "Parker", role = "aut", comment = c(ORCID = "https://orcid.org/0000-0003-2995-5284")) )
Description: The ManyEcoEvo package provides a set of functions for aiding data cleaning, preparation and conducting analysis for multi-analyst style studies. It also contains datasets from the ManyEcoEvo project for reproducing the ManyEcoEvo analysis.
License: GPL (>= 3)
Depends: R (>= 2.10)
Imports: betapart, dplyr, tidyselect, pointblank, tibble, cli, data.table,
forcats, fs, glue, here, lme4, metafor, naniar, magrittr, tidyr, rlang,
purrr, tidyselect,
Suggests: targets, broom.mixed, metaviz, ggeffects, parameters, performance,
parsnip, workflows, timetk, recipes, sae, pracma, progress, knitr,
rmarkdown
Encoding: UTF-8
LazyData: true
Roxygen: list(markdown = TRUE)
RoxygenNote: 7.3.1
URL: https://github.com/egouldo/ManyEcoEvo,
https://egouldo.github.io/ManyEcoEvo/
BugReports: https://github.com/egouldo/ManyEcoEvo/issues
VignetteBuilder: knitr
Author: Elliot Gould [aut, cre] (<https://orcid.org/0000-0002-6585-538X>), Hannah S. Fraser [aut] (<https://orcid.org/0000-0003-2443-4463>), Shinichi Nakagawa [aut] (<https://orcid.org/0000-0002-7765-5182>), Timothy H. Parker [aut] (<https://orcid.org/0000-0003-2995-5284>)
Maintainer: Elliot Gould <elliot.gould@unimelb.edu.au>
Built: R 4.4.0; ; 2024-06-16 07:39:45 UTC; unix
RemoteType: local
RemoteUrl: ~/Documents/GitHub/ManyEcoEvo_1.5.0.9000.tgz
Remotes: daniel1noble/orchaRd, NightingaleHealth/ggforestplot
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Z_VZ_preds Calculate Z and VZ of out-of-sample predictions
anonymise_teams Anonymise ManyEcoEvo Data
apply_VZ_exclusions Apply VZ exclusion to a data-frame containing
list-columns of yi subsets
apply_sorensen_calc Applies the sorensen diversity index
calculation to variable diversity dataset
apportion_heterogeneity_ml
Apportion heterogeneity of a multi-level
meta-analytic model
assign_transformation_type
Assign back-transformation type to be applied
to analysis point-estimates
augment_prediction_data
Augment analyst out-of-sample prediction data
according to the outcome of pointblank
interrogation
back_transform_response_vars_yi
Back Transform Response Variables - yi
box_cox_transform Box-cox transform absolute deviation from the
meta-analytic mean scores
calc_I2_ml Calculate I2 for a multilevel meta-analytic
model
calculate_deviation_score
Calculate deviation from meta-analytic mean
calculate_sorensen_diversity_index
Calculate mean sorensen diversity index values
for an analyst dataset
capwords Capitalise Words
clean_response_transformation
Clean response transformation variable
compare_ml_MA Compare two fitted multi-level models
compute_MA_inputs Compute meta-analysis inputs for a
nested-dataframe containing different
datasets/subsets of analyst data
compute_metaanalysis_inputs
Compute all metaanalysis inputs for different
types of estimates
conversion Conditionally apply back-transformation
conversion_2 Conditionally apply back-transformation
convert_predictions Convert Predictions
count_analyses_variables_used
Count number of analyses each variable is used
count_binary_coded_features
Summarise binary coded features of analyses
count_teams_analyses Summarise number of analyst teams and total
analyses per dataset
cube_back Back transform beta estimates for models with
$x^3$-link
divide_back Back transform beta estimates or out-of-sample
predictions from models whose response variable
has been divided by some number
est_to_zr Convert estimate to Zr
exclude_extreme_VZ Exclude extreme values of VZ from a dataframe
of standardised predictions
fit_boxcox_ratings_cat
Fit model of boxcox deviation scores as
function of continuous ratings
fit_boxcox_ratings_cont
Fit model of boxcox deviation scores as
function of continuous ratings
fit_boxcox_ratings_ord
Fit model of boxcox deviation scores as
function of continuous ratings
fit_metafor_mv Fit Multivariate Metaregression using metafoR
fit_metafor_mv_reduced
Fit reduced multivariate metaregression model
fit_metafor_uni Fit univariate meta-analysis with metafor
fit_sorensen_glm Fit univariate glm of deviation scores on
sorensen diversity index
fit_uni_mixed_effects Fit univariate glm of deviation scores on
random effects inclusion
generate_collinearity_subset
Generate Collinearity Data Subset
generate_exclusion_subsets
Generate subsets of analyst data based on
different exclusion criteria
generate_expertise_subsets
Generate Expertise Data Subsets
generate_outlier_subsets
Generate Outlier Subsets for ManyEcoEvo
datasets
generate_rating_subsets
Generate subsets of ManyEcoEvo Data based on
Peer Review Ratings
generate_yi_subsets Generate subsets of out-of-sample predictions
data by 'estimate_type' for multiple analysis
datasets.
get_MA_fit_stats Extract meta-analytic statistics like I^2, etc.
get_diversity_data Get Diversity Data
gg_forest Forestplot with ggplot2
i2_ml i2_ml
identity_back Back transform beta estimates for models with
identity-link
inverse_back Back transform beta estimates for models with
$1/x$ link
log_back Back transform beta estimates for models with
log-link
log_transform log transform response-scale yi estimates
logit_back Back transform beta estimates for models with
logit-link
make_param_table Make paramater table
make_viz Make visualisations wrapper function
meta_analyse_datasets Meta-analyses multiple datasets or subsets of
datasets of analyst data
named_group_split Split data frame by groups and name elements
plot_cont_rating_effects
Plot Marginal Effects for Numeric Rating Model
plot_effects_diversity
Marginal Effects Plot of Diversity Index Model
plot_model_means_box_cox_cat
plot_model_means_box_cox_cat
plot_model_means_orchard
plot_model_means_orchard
power_back Back transform beta estimates for models with
power-link
pred_to_Z Standardize Out-Of-Sample Predictions
prepare_ManyEcoEvo Prepare ManyEcoEvo raw dataset
prepare_ManyEcoEvo_yi Prepare ManyEcoEvo raw dataset for
out-of-sample predictions
prepare_diversity_raw Prepare diversity index data
prepare_response_variables
Prepare response variable data for nested
ManyEcoEvo dataset
prepare_response_variables_yi
Prepare response variable data for nested
ManyEcoEvo dataset - out of sample predictions
only
prepare_review_data Prepare peer-review data from Qualtrics
preprocess_prediction_files
Preprocess Prediction Files
preprocess_updated_prediction_files
Performs QA on re-submitted out-of-sample
prediction files
probit_back Back transform beta estimates for models with
probit-link
read_submission_data Read out-of-sample-prediction analyst
submission data
rm_inf_na Removes infinite and NA values from a dataframe
of standardised effects
run_model_checks Perform model checking on series of fitted
models for different datasets, exclusion sets
and estimate types
square_back Back transform beta estimates for models with
$x^2$-link
square_root_back Back transform beta estimates or out-of-sample
predictions from models whose response variable
has been transformed by the square root
standardise_response Standardise Response Variable
subset_fns_Zr Subsetting Functions for Zr analysis
subset_fns_yi Subsetting Functions for yi analysis
summarise_analyses_by_reviewer
Summarise analyses reviewed by reviewer
summarise_analysis_types
Summarise Analysis Types
summarise_conclusions Summarise counts of qualitative conclusions
across all datasets
summarise_conclusions_data
Count qualitative conclusions across all
analyses for each dataset
summarise_model_composition
Summarise Model Composition
summarise_model_composition_data
Summarise model composition for a single
dataframe of out of sample predictions or out
or effect sizes
summarise_reviews Summarise Peer-Reviews
summarise_reviews_per_analysis
Summarise reviews per each analysis
summarise_sorensen_index
Summarise Mean Sorensen's Index Estimates
summarise_sorensen_index_data
Summarise Sorensen's Mean Index Estimates for a
dataframe
summarise_variable_counts
Summarise variable usage across analyses
validate_predictions Validate predictions conditioned on dataset
validate_predictions_df_blue_tit
Validate out of sample predictions for blue tit
dataset with pointblank package
validate_predictions_df_euc
Validate out of sample predictions for
eucalytpus dataset with pointblank package
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