est.ss: est.ss

Description

Function to estimate studies sample size by maximizing different conservative estimates. Performs four different extraction heuristics for sample sizes mentioned in abstract, text and statistical results.

Usage

est.ss(
  abstract = NULL,
  text = NULL,
  stats = NULL,
  standardStats = NULL,
  quantileDF = 0.9,
  max.only = FALSE,
  max.parts = TRUE
)

Value

Numeric vector with extracted sample sizes by input and estimated sample size.

Arguments

abstract: an abstract text string.
text: the main text string to process (usually method and result sections). If text has content, arguments "stats" and "standardStats" are deactivated and filled with results by get.stats(text).
stats: statistics extracted with get.stats(x)$stats (only active if no text is submitted).
standardStats: standard statistics extracted with get.stats(x)$standardStats (only active if no text is submitted).
quantileDF: quantile of (df1-1)+(df2+2) to extract.
max.only: Logical. If TRUE only the final estimate will be returned, if FALSE all sub estimates are returned as well.
max.parts: Logical. If FALSE outputs all captured sample sizes in sub inputs.

Details

Sample size extraction from abstract:
- Extracts N= from abstract text and performs position-of-speech search with list of synonyms of sample units

Sample size extraction from text:
- Unifies and extracts textlines with age descriptions, than computes sum of hits as nage - Unifies and extracts all "numeric male-female" patterns than computes sum of first male/female hit - Unifies and extracts textlines with participant description than computes sum of first three hits as ntext

Sample size extraction from statistical results:
- Extracts "N=" in statistical results extracted with allStats() that contain p-value: e.g.: chi(2, N=12)=15.2, p<.05

Sample size extraction by degrees of freedom with result of standardStats(allStats()):
- Extracts df1 and df2 if possible and neither containing a ".", than calculates specified quantile of (df1+1)+(df2+2) (at least 2 group comparison assumed)

Examples

Run this code

# \donttest{
 a<-"One hundred twelve students participated in our study."
 est.ss(abstract=a)
 x<-"Our sample consists of three hundred twenty five undergraduate students.
     The F-test indicates significant differences in means F(2,102)=3.21, p<.05."
 est.ss(text=x)
# }