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compute.es (version 0.2-2)

a.tes: t-test Value from ANCOVA to Effect Size

Description

Converts a t-test value from ANCOVA to an effect size of $d$ (mean difference), $g$ (unbiased estimate of $d$), $r$ (correlation coefficient), $z'$ (Fisher's $z$), and log odds ratio. The variances, confidence intervals and p-values of these estimates are also computed, along with NNT (number needed to treat), U3 (Cohen's $U_(3)$ overlapping proportions of distributions), CLES (Common Language Effect Size) and Cliff's Delta.

Usage

a.tes(t, n.1, n.2, R, q, level=95, dig=2, id=NULL, data=NULL)

Arguments

t
t-test value reported in primary study.
n.1
Treatment group sample size.
n.2
Comparison group sample size.
R
Covariate outcome correlation or multiple correlation.
q
number of covariates.
level
Confidence level. Default is 95%.
dig
Number of digits to display. Default is 2 digits.
id
Study identifier. Default is NULL, assuming a scalar is used as input. If input is a vector dataset (i.e., data.frame, with multiple values to be computed), enter the name of the study identifier here.
data
name of data.frame. Default is NULL, assuming a scalar is used as input. If input is a vector dataset (i.e., data.frame, with multiple values to be computed), enter the name of the data.frame here.

Value

  • dStandardized mean difference ($d$).
  • var.dVariance of $d$.
  • l.dlower confidence limits for $d$.
  • u.dupper confidence limits for $d$.
  • U3.dCohen's $U_(3)$, for $d$.
  • cl.dCommon Language Effect Size for $d$.
  • cliffs.dCliff's Delta for $d$.
  • p.dp-value for $d$.
  • gUnbiased estimate of $d$.
  • var.gVariance of $g$.
  • l.glower confidence limits for $g$.
  • u.gupper confidence limits for $g$.
  • U3.gCohen's $U_(3)$, for $g$.
  • cl.gCommon Language Effect Size for $g$.
  • p.gp-value for $g$.
  • rCorrelation coefficient.
  • var.rVariance of $r$.
  • l.rlower confidence limits for $r$.
  • u.rupper confidence limits for $r$.
  • p.rp-value for $r$.
  • zFisher's z ($z'$).
  • var.zVariance of $z'$.
  • l.zlower confidence limits for $z'$.
  • u.zupper confidence limits for $z'$.
  • p.zp-value for $z'$.
  • OROdds ratio.
  • l.orlower confidence limits for $OR$.
  • u.orupper confidence limits for $OR$.
  • p.orp-value for $OR$.
  • lORLog odds ratio.
  • var.lorVariance of log odds ratio.
  • l.lorlower confidence limits for $lOR$.
  • u.lorupper confidence limits for $lOR$.
  • p.lorp-value for $lOR$.
  • N.totalTotal sample size.
  • NNTNumber needed to treat.

References

Borenstein (2009). Effect sizes for continuous data. In H. Cooper, L. V. Hedges, & J. C. Valentine (Eds.), The handbook of research synthesis and meta analysis (pp. 279-293). New York: Russell Sage Foundation. Cohen, J. (1988). Statistical power for the behavioral sciences (2nd ed.). Hillsdale, NJ: Erlbaum. Furukawa, T. A., & Leucht, S. (2011). How to obtain NNT from Cohen's d: comparison of two methods. PloS one, 6(4), e19070. McGraw, K. O. & Wong, S. P. (1992). A common language effect size statistic. Psychological Bulletin, 111, 361-365. Valentine, J. C. & Cooper, H. (2003). Effect size substantive interpretation guidelines: Issues in the interpretation of effect sizes. Washington, DC: What Works Clearinghouse.

See Also

tes