dat.metap {metap}

Example data

Description

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

Usage

data(dat.metap)

Format

A list with the following elements:

beckerp

A vector of length 5 hypothetical \(p\) values

cholest

A data frame with 34 observations on the following 5 variables.

ntreat

A numeric vector of numbers in the treated group

ncontrol

A numeric vector of number in the control group

dtreat

A numeric vector of number of deaths in the treated group

dcontrol

A numeric vector of number of deaths in the control group

p

a numeric vector of one sided \(p\) values

edgington

A vector of length 7 hypothetical \(p\) values

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 of \(p\) values

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 hypothetical \(p\) values

validity

A data frame with 20 observations on the following 3 variables

n

A numeric vector of sample sizes

r

a numeric vector of correlation coefficients

p

a numeric vector of one sided \(p\) values

zhang

A data frame with 22 observations on the following 11 variables

study

character, the study names

smd

numeric, the standardised mean difference

lo

numeric, the lower confidence limit

hi

numeric, the upper confidence limit

ntreat

numeric, the treated sample size

ncont

numeric, the control sample size

n

numeric, the total sample size

phase

factor, what phase the patients were in: acute, healing, healed

sd

numeric, the calculated standard deviation

z

numeric, the calculated z

p

numeric, the probability associated with z

Details

beckerp

Hypothetical \(p\) values from Becker (1994)

cholest

\(p\) values from trials of interventions for cholesterol lowering from Sutton et al. (2000)

edgington

Hypothetical \(p\) values from Edgington (1972)

mourning

Results from a study of mourning practices of Israeli youth following the assassination of Itzakh Rabin from Benjamini and Hochberg (2000)

naep

Results of mathematical achievment scores from the National Assessment of Educational Progress from Benjamini and Hochberg (2000)

rosenthal

Hypothetical example from Rosenthal (1978)

teachexpect

\(p\)-values from studies of the effect of manipulating teacher expectancy on student IQ from Becker (1994)

validity

Data from studies of validity of student ratings of their instructors from Becker (1994) including correlations and sample sizes as well as \(p\)-values

zhang

Data from trials of exercise training for patients with cardiovascular disease from Zhang et al. (2016)

Note

The \(p\)-values in cholest have been re-calculated from other data given in the book and so are of higher accuracy than the ones given in the book which are only to two decimal places.

Author(s)

Michael Dewey

References

Becker BJ (1994). “Combining significance levels.” In Cooper H, Hedges LV (eds.), A handbook of research synthesis, 215–230. Russell Sage, New York.

Benjamini Y, Hochberg Y (2000). “On the adaptive control of the false discovery rate in multiple testing with independent statistics.” Journal of Educational and Behavioral Statistics, 25, 60–83.

Edgington ES (1972). “An additive method for combining probability values from independent experiments.” Journal of Psychology, 80, 351–363.

Rosenthal R (1978). “Combining results of independent studies.” Psychological Bulletin, 85, 185–193.

Sutton AJ, Abrams KR, Jones DR, Sheldon TA, Song F (2000). Methods for meta-analysis in medical research. Wiley, Chichester.

Zhang YM, Lu Y, Yang D, Wu HF, Bian ZP, Xu JD, Gu CR, Wang LS, Chen XJ (2016). “The effects of different initiation time of exercise training on left ventricular remodeling and cardiopulmonary rehabilitation in patients with left ventricular dysfunction after myocardial infarction.” Disability and Rehabilitation, 38, 268–276.

Examples

data(dat.metap)