calculate_binom_baseline

dataframe in output from <code><a rd-options="" href="/link/reshape_for_binomials?package=GenderInfer&version=0.1.0" data-mini-rdoc="GenderInfer::reshape_for_binomials">reshape_for_binomials</a></code>
containing the columns: female, male, which contain the integer counts of 
males and females respectively and must be a numeric vector greater than 0.

data_df, 

female baseline in percentage from <code><a rd-options="" href="/link/baseline?package=GenderInfer&version=0.1.0" data-mini-rdoc="GenderInfer::baseline">baseline</a></code>.

baseline_female, 

confidence level to use for significance calculation,
default is 0.95

confidence_level, 

Function to calculate the lower CI, upper CI, percentages and 
counts, and significance of difference from one or multiple baseline 
percentages, given supplied confidence level using

Implementation of functions, which combines binomial calculation
and data visualisation, to analyse the differences in publishing authorship
by gender described in Day et al. (2020) <doi:10.1039/C9SC04090K>.
It should only be used when self-reported gender is unavailable.

Rita Giordano

GenderInfer

This is a Collection of Functions to Analyse Gender Differences

Aileen Day

John Boyle

Colin Batchelor

Royal Society of Chemistry 

calculate_binom_baseline function

dataframe in output from <code><a rd-options='' href='reshape_for_binomials'>reshape_for_binomials</a></code>
containing the columns: female, male, which contain the integer counts of 
males and females respectively and must be a numeric vector greater than 0.

female baseline in percentage from <code><a rd-options='' href='baseline'>baseline</a></code>.

calculate_binom_baseline: Calculate binomials and significance for multiple baselines.

Description

Usage

Arguments

Value