Calculate power and required sample size for a given power to detect incidence change.
incpower( I1, I2, PrevH1, PrevH2, n1 = "both", n2 = "both", alpha = 0.05, Power = 0.8, SS = "out", CR = 1, DE_H = 1, DE_R = 1, BMest = "same.test", MDRI, RSE_MDRI, FRR, RSE_FRR, BigT = 730, Boot = FALSE, BS_Count = 1e+05, Cov.PrevH.I = c(0, 0), debug = FALSE )
| I1 | Predicted incidence of HIV in survey 1. |
|---|---|
| I2 | Predicted incidence of HIV in survey 2. |
| PrevH1 | Predicted prevalence of HIV in survey 1. |
| PrevH2 | Predicted prevalence of HIV in survey 2. |
| n1 | Sample size for survey 1. If equal sample sizes for both surveys are desired at a given power level, both n1 and n2 must have value 'both', which is the default. |
| n2 | Sample size for survey 2. If equal sample sizes for both surveys are desired at a given power level, both n1 and n2 must have value 'both', which is the default. |
| alpha | Significance level for test (default alpha=0.05). |
| Power | Desired power used to calculate a sample size for the surveys. Default is 0.80, meaning the function outputs the necessary sample size to achieve stated power for a test of differences in incidence. If Power is set to 'out', function will return power of detecting a difference in incidences for given sample size inputs. |
| SS | Sample size. Default is 'out', meaning the function takes a power argument and outputs a common sample size needed to achieve power level for test of differences for incidence. If power is desired for a given sample size, parameter value is irrelevant; however, values for n1 and n2 must be specified. |
| CR | Coverage rate (0-1). |
| DE_H | Design effect of HIV prevalence test (vector/integer). If a single value is specified, that value is assumed to be the value for both surveys. |
| DE_R | Design effect of recency test (vector/integer). If a single value is specified, that value is assumed to be the value for both surveys. |
| BMest | Biomarker test parameter (MDRI, FRR, and RSE) estimation by one the 3 options 'same.test'(default), 'FRR.indep', 'MDRI.FRR.indep' (string). |
| MDRI | mean duration of recent infection [days] (vector/integer). If a single value is specified, that value is assumed to be the value for both surveys. |
| RSE_MDRI | Relative standard error of MDRI [days] (vector/integer). If a single value is specified, that value is assumed to be the value for both surveys. |
| FRR | False recent rate (vector/integer). If a single value is specified, that value is assumed to be the value for both surveys. |
| RSE_FRR | Relative standard error of FRR (vector/integer). If a single value is specified, that value is assumed to be the value for both surveys. |
| BigT | Post-infection time cut-off (days). Default 730. If a single value is specified, that value is assumed to be the value for both surveys. |
| Boot | True/False variable indicating whether variance of point estimates is to be calculated by Empirical Bootstrapping (TRUE) or Delta Method (FALSE), the default setting. |
| BS_Count | Specifies number of bootstrap samples for bootstrapped confidence intervals of incidence. |
| Cov.PrevH.I | Covariance of prevalence and incidence for bootstrap resampling. |
| debug | Enable debugging mode (browser) |
Common sample size of two surveys--or the sample size of one survey given the other has already been completed--necessary to achieve a given power level for testing a null hypothesis that the incidence rates are identical between populations; alternatively, the power of said test under a particular sample size scenario. Function also returns implied statistics from input values on paramters, confidence limits, and population counts.
The package contains long form documentation in the form of vignettes that cover the use of the main fucntions. Use browseVignettes(package="inctools") to access them.
incpower(I1 = 0.05, I2 = 0.03, PrevH1 = 0.20, PrevH2 = 0.20, n1 = 5000, n2 = 5000, alpha = 0.05, Power = "out", SS = NULL, DE_H = c(1,1.1), DE_R = 1, BMest = 'same.test', MDRI = 200, RSE_MDRI = 0.05, FRR = 0.01, RSE_FRR = 0.20, BigT = 730)#> $Inc.Difference.Statistics #> # A tibble: 1 x 7 #> deltaI_Est RSE_deltaI RSE_deltaI.infSS Power Power.infSS CI.low #> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> #> 1 0.02 0.330375 0.0524443 0.856991 1 0.00704953 #> # … with 1 more variable: CI.up <dbl> #> #> $Implied.Incidence.Statistics #> # A tibble: 2 x 5 #> Survey Given.I RSE_I CI.low CI.up #> <dbl> <dbl> <dbl> <dbl> <dbl> #> 1 1 0.05 0.115105 0.0387199 0.0612801 #> 2 2 0.03 0.146949 0.0213596 0.0386404 #> #> $Implied.MDRI.Statistics #> # A tibble: 1 x 3 #> Given.MDRI CI.low CI.up #> <dbl> <dbl> <dbl> #> 1 200 180.400 219.600 #> #> $Implied.FRR.Statistics #> # A tibble: 1 x 3 #> Given.FRR CI.low$CI.low CI.up$CI.up #> <dbl> <dbl> <dbl> #> 1 0.01 0.00608007 0.0139199 #> #> $Implied.Subject.Counts #> # A tibble: 4 x 2 #> Survey.1 Survey.2 #> <dbl> <dbl> #> 1 4000 4000 #> 2 1000 1000 #> 3 1000 1000 #> 4 116 73 #>incpower(I1 = 0.05, I2 = 0.03, PrevH1 = 0.20, PrevH2 = 0.20, alpha = 0.05, Power = 0.80, SS = "out", DE_H = 1, DE_R = 1, BMest = 'FRR.indep', MDRI = 200, RSE_MDRI = 0.05, FRR = c(0.01,0.009), RSE_FRR = c(0.20,0.21), BigT = 730)#> $Minimum.Common.SS #> [1] 4297 #> #> $Inc.Difference.Statistics #> # A tibble: 1 x 7 #> deltaI_Est RSE_deltaI RSE_deltaI.infSS Power Power.infSS CI.low #> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> #> 1 0.02 0.356937 0.0684299 0.800007 1 0.00600831 #> # … with 1 more variable: CI.up <dbl> #> #> $Implied.Incidence.Statistics #> # A tibble: 2 x 5 #> Survey Given.I RSE_I CI.low CI.up #> <dbl> <dbl> <dbl> <dbl> <dbl> #> 1 1 0.05 0.122291 0.0380157 0.0619843 #> 2 2 0.03 0.155000 0.0208862 0.0391138 #> #> $Implied.MDRI.Statistics #> # A tibble: 1 x 3 #> Given.MDRI CI.low CI.up #> <dbl> <dbl> <dbl> #> 1 200 180.400 219.600 #> #> $Implied.FRR.Statistics #> # A tibble: 2 x 3 #> Given.FRR CI.low$CI.low CI.up$CI.up #> <dbl> <dbl> <dbl> #> 1 0.01 0.00608007 0.0139199 #> 2 0.009000 0.00529567 0.0127043 #> #> $Implied.Subject.Counts #> # A tibble: 4 x 2 #> Survey.1 Survey.2 #> <dbl> <dbl> #> 1 3438 3438 #> 2 859 859 #> 3 859 859 #> 4 99 62 #>