Description Usage Arguments Value Examples
Function to calculate sample size for estimating prevalence/proportional indicators from a simple random sample (SRS) or a random cluster sample (RCS) survey. This function has an option to apply a finite population correction (FPC) to the sample size calculations.
1 2 | get_ss_prevalence(z = 1.96, p = 0.5, c = 0.1, deff = 2,
fpc = FALSE, pop = NULL)
|
z |
The z-score/z-value for a 95% confidence interval. Typical vaues
for |
p |
The numeric value of the expected prevalence/proportion. Default is
0.5 (for 50% prevalence/proportion) as this gives the highest sample
size estimate. If previous prevalence/proportion is known, this value
can be used for |
c |
The numeric value of the desired precision of the resulting prevalence/proportion estimate. For coverage surveys, default is set at ±10% (0.1). |
deff |
The numeric for design effect ( |
fpc |
Logical. Default FALSE. If TRUE, finite population correct (FPC) is applied. |
pop |
Population size from which sample has been drawn from. If
|
A numeric value for sample size required to estimate the required prevalence/proportion.
1 2 3 4 | # Calculate sample size to estimate a proportion with 95% confidence
# interval, an expected proporition of 50%, precision of 10% and a design
# effect of 2
get_ss_prevalence(z = 1.96, p = 0.5, c = 0.1, deff = 2)
|
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