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compute.es (version 0.2-2)

a.mes: Mean Values from ANCOVA F-statistic to Effect Size

Description

Converts an ANCOVA F-statistic 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.mes(m.1.adj, m.2.adj, sd.adj, n.1, n.2, R, q, level=95, dig=2, id=NULL, data=NULL)

Arguments

m.1.adj
Adjusted mean of treatment group from ANCOVA.
m.2.adj
Adjusted mean of comparison group from ANCOVA.
sd.adj
Adjusted standard deviation.
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

mes, mes2, a.mes2