This function calculated odds ratios based on various type of input/information, as described in Table 11.10 from Borenstein and Hedges (2019, p. 226).
Usage
OR_calc(
A = NULL,
B = NULL,
C = NULL,
D = NULL,
p1 = NULL,
p2 = NULL,
n1 = NULL,
n2 = NULL,
OR = NULL,
LL_OR = NULL,
UL_OR = NULL,
SE_OR = NULL,
V_OR = NULL,
Z = 1.96,
ICC = NULL,
avg_cl_size = NULL,
n_cluster_arms = 2,
add_name_to_vars = NULL,
vars = dplyr::everything()
)Arguments
- A
Upper left cell of an 2 X 2 frequency table.
- B
Upper right cell of an 2 X 2 frequency table.
- C
Lower left cell of an 2 X 2 frequency table.
- D
Lower right cell of an 2 X 2 frequency table.
- p1
Risk/probability of an event in group 1 (usually the treatment group).
- p2
Risk/probability of an event in group 2 (usually the control group).
- n1
Sample size of group 1 (usually the treatment group).
- n2
Sample size of group 2 (usually the control group).
- OR
Odds ratio estimate.
- LL_OR
Lower bound of the 95% confidence interval of the odds ratio.
- UL_OR
Upper bound of the 95% confidence interval of the odds ratio.
- SE_OR
Standard error of the odds ratio.
- V_OR
Sampling variance of the odds ratio.
- Z
Z-values from an normal distribution.
- ICC
Intra-class correlation.
- avg_cl_size
Average cluster size.
- n_cluster_arms
(Optional) Number of arm with clustering.
- add_name_to_vars
Optional character string to be added to the variables names of the generated
tibble.- vars
Variables to be reported. Default is
NULL. See Value section for further details.
References
Borenstein and Hedges (2019). Effect sizes for meta-analysis. In H. Cooper, L. V. Hedges, & J. C. Valentine (Eds.), The handbook of research synthesis and meta-analysis (3rd ed., pp. 207–242). Russell Sage Foundation West Sussex.
Hedges, L. V., & Citkowicz, M (2015). Estimating effect size when there is clustering in one treatment groups. Behavior Research Methods, 47(4), 1295-1308. doi:10.3758/s13428-014-0538-z
Higgins, J. P. T., Eldridge, S., & Li, T. (2019). In J. P. T. Higgins, J. Thomas, J. Chandler, M. S. Cumpston, T. Li, M. Page, & V. Welch (Eds.), Cochrane handbook for systematic reviews of interventions (2nd ed., pp. 569–593). Wiley Online Library. doi:10.1002/9781119536604.ch23
Examples
# Using raw events
OR_calc(A = 20, B = 80, C = 10, D = 90)
#> # A tibble: 1 × 3
#> OR ln_OR vln_OR
#> <dbl> <dbl> <dbl>
#> 1 2.25 0.811 0.174
# Using proportions
OR_calc(p1 = .2, p2 = .1, n1 = 100, n2 = 100)
#> # A tibble: 1 × 3
#> OR ln_OR vln_OR
#> <dbl> <dbl> <dbl>
#> 1 2.25 0.811 0.174
# Using raw OR and CIs
OR_calc(OR = 2.25, LL_OR = 1.5, UL_OR = 3)
#> # A tibble: 1 × 3
#> OR ln_OR vln_OR
#> <dbl> <dbl> <dbl>
#> 1 2.25 0.811 0.0313
# Adding suffix to variables and selecting specific variables
OR_calc(A = 20, B = 80, C = 10, D = 90, add_name_to_vars = "_test", vars = OR_test)
#> # A tibble: 1 × 1
#> OR_test
#> <dbl>
#> 1 2.25
# Cluster bias adjustment when there is clustering in both groups
OR_calc(p1 = .53, p2 = .11, n1 = 20, n2 = 26, ICC = 0.1, avg_cl_size = 8, n_cluster_arms = 2)
#> # A tibble: 1 × 5
#> OR ln_OR vln_OR DE vln_OR_C
#> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 9.12 2.21 0.594 1.7 1.01
# Cluster bias adjustment when there is clustering in one group only
OR_calc(p1 = .53, p2 = .11, n1 = 20, n2 = 26, ICC = 0.1, avg_cl_size = 8, n_cluster_arms = 1)
#> # A tibble: 1 × 5
#> OR ln_OR vln_OR DE vln_OR_C
#> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 9.12 2.21 0.594 1.35 0.803