package-data: Example data

Description

The package contains the following datasets: beckerp, cholest, edgington, mourning, naep, rosenthal, teachexpect, and validity.

Usage

data(beckerp)
data(cholest)
data(edgington)
data(mourning)
data(naep)
data(rosenthal)
data(teachexpect)
data(validity)

Arguments

Format

beckerp

A vector of length 5

cholest

A vector of length 34

edgington

A vector of length 7

naep

A data frame with 34 observations on the following 2 variables.

state: a factor with levels AL AR AZ CA CO CT DE FL GA HI IA ID IN KY LA MD MI MN NC ND NE NH NJ NM NY OH OK PA RI TX VA WI WV WY
p: a numeric vector

mourning

A data frame with 9 observations on the following 3 variables.

stance: a factor with levels No stand Opponent Supporter
grade: a factor with levels G11-12 G7-8 G9-10
p: a numeric vector

rosenthal

A data frame with 5 observations on the following 3 variables.

t: A numeric vector of values of $t$
df: a numeric vector of degrees of freedom
p: a numeric vector of one sided $p$ values

teachexpect

A vector of length 19

validity

A vector of length 20

Details

beckerp: Hypothetical $p$ values from Becker
cholest: $p$-values from studies of cholesterol lowering from Sutton
edgington: Hypothetical $p$ values from Edgington
mourning: Results from a study of mourning practices of Israeli youth from Benjamini
naep: Results on the National Assessment of Educational Progress from Benjamini
rosenthal: Hypothetical example from Rosenthal
teachexpect: $p$-values from studies of the effect of manipulating teacher expectancy from Becker
validity: $p$-values from studies of validity of student ratings from Becker

References

Becker, B J. Combining significance levels. In Cooper, H and Hedges, L V, editors A handbook of research synthesis, chapter 15, pages 215--230. Russell Sage, New York, 1994.

Benjamini, Y and Hochberg, Y. On the adaptive control of the false disovery rate in multiple testing with independent statistics. Journal of Educational and Behavioral Statistics, 25: 60--83, 2000.

Edgington, E S. An additive method for combining probability values from independent experiments. Journal of Psychology, 80:351-363, 1972.

Rosenthal, R. Combining the results of independent studies. Psychological Bulletin, 85:185--193, 1978.

Sutton A J, Abrams, K R, Jones D R, Sheldon T A and Song, F. Methods for meta-analysis in medical research. Wiley, Chichester, 2000.