es_from_ancova_means_sd {metaConvert} | R Documentation |
Convert means and standard deviations of two independent groups obtained from an ANCOVA model into several effect size measures
Description
Convert means and standard deviations of two independent groups obtained from an ANCOVA model into several effect size measures
Usage
es_from_ancova_means_sd(
n_exp,
n_nexp,
ancova_mean_exp,
ancova_mean_nexp,
ancova_mean_sd_exp,
ancova_mean_sd_nexp,
cov_outcome_r,
n_cov_ancova,
smd_to_cor = "viechtbauer",
reverse_ancova_means
)
Arguments
n_exp |
number of participants in the experimental/exposed group. |
n_nexp |
number of participants in the non-experimental/non-exposed group. |
ancova_mean_exp |
adjusted mean of participants in the experimental/exposed group. |
ancova_mean_nexp |
adjusted mean of participants in the non-experimental/non-exposed group. |
ancova_mean_sd_exp |
adjusted standard deviation of participants in the experimental/exposed group. |
ancova_mean_sd_nexp |
adjusted standard deviation of participants in the non-experimental/non-exposed group. |
cov_outcome_r |
correlation between the outcome and covariate(s) (multiple correlation when multiple covariates are included in the ANCOVA model). |
n_cov_ancova |
number of covariates in the ANCOVA model. |
smd_to_cor |
formula used to convert the adjusted |
reverse_ancova_means |
a logical value indicating whether the direction of the generated effect sizes should be flipped. |
Details
This function first computes an "adjusted" mean difference (MD), Cohen's d (D) and Hedges' g (G) from the adjusted means and standard deviations. Odds ratio (OR) and correlation coefficients (R/Z) are then converted from the Cohen's d.
This function start by estimating the non-adjusted standard deviation of the two groups (formula 12.24 in Cooper);
mean\_sd\_exp = \frac{ancova\_mean\_sd\_exp}{\sqrt{1 - cov\_outcome\_r^2}}
mean\_sd\_nexp = \frac{ancova\_mean\_sd\_nexp}{\sqrt{1 - cov\_outcome\_r^2}}
To obtain the mean difference, the following formulas are used (authors calculations):
md = ancova\_mean\_exp - ancova\_mean\_nexp
md\_se = \sqrt{\frac{mean\_sd\_exp^2}{n\_exp} + \frac{mean\_sd\_nexp^2}{n\_nexp}}
md\_ci\_lo = md - md\_se * qt(.975, n\_exp+n\_nexp-2-n\_cov\_ancova)
md\_ci\_up = md + md\_se * qt(.975, n\_exp+n\_nexp-2-n\_cov\_ancova)
To obtain the Cohen's d, the following formulas are used (table 12.3 in Cooper):
mean\_sd\_pooled = \sqrt{\frac{(n\_exp - 1) * ancova\_mean\_exp^2 + (n\_nexp - 1) * ancova\_mean\_nexp^2}{n\_exp+n\_nexp-2}}
cohen\_d = \frac{ancova\_mean\_exp - ancova\_mean\_nexp}{mean\_sd\_pooled}
cohen\_d\_se = \frac{(n\_exp+n\_nexp)*(1-cov\_outcome\_r^2)}{n\_exp*n\_nexp} + \frac{cohen\_d^2}{2(n\_exp+n\_nexp)}
cohen\_d\_ci\_lo = cohen\_d - cohen\_d\_se * qt(.975, n\_exp + n\_nexp - 2 - n\_cov\_ancova)
cohen\_d\_ci\_up = cohen\_d + cohen\_d\_se * qt(.975, n\_exp + n\_nexp - 2 - n\_cov\_ancova)
To estimate other effect size measures,
Calculations of the es_from_cohen_d_adj()
are applied.
Value
This function estimates and converts between several effect size measures.
natural effect size measure | MD + D + G |
converted effect size measure | OR + R + Z |
required input data | See 'Section 19. Adjusted: Means and dispersion' |
https://metaconvert.org/html/input.html | |
References
Cooper, H., Hedges, L.V., & Valentine, J.C. (Eds.). (2019). The handbook of research synthesis and meta-analysis. Russell Sage Foundation.
Examples
es_from_ancova_means_sd(
n_exp = 55, n_nexp = 55,
ancova_mean_exp = 2.3, ancova_mean_sd_exp = 1.2,
ancova_mean_nexp = 1.9, ancova_mean_sd_nexp = 0.9,
cov_outcome_r = 0.2, n_cov_ancova = 3
)