Exponential logit model for two variables

Fit a logit model of v.density on v.fever v.density with a exponential coefficient for the v.density

Usage

logitexp(v.fever, v.density)

Arguments

v.fever

numeric vector of 0/1 indicating fever or equivalent

v.density

numeric vector of values >= 0 indicating the density

Value

S3 object of class afmodel with 4 components: data, model, coefficients and the estimated attributable fraction.

Details

logit(v.fever) ~ beta * (v. density ^ tau)

This corresponds to the model 3 describe by Smith, T., Schellenberg, J.A., Hayes, R., 1994. Attributable fraction estimates and case definitions for malaria in endemic areas. Stat Med 13, 2345–2358.

See also

senspec

Examples

{
# Get the sample data
head(malaria_df1)
fit <- logitexp(malaria_df1$fever, malaria_df1$density)
fit
senspec(fit,  c(1,100,500,1000,2000,4000,8000,16000, 32000,54000,100000))
}
#>       cutoff sensitivity specificity       ppv       npv
#>  [1,]      1   1.0000000   0.7727793 0.7658522 1.0000000
#>  [2,]    100   0.9986640   0.7851102 0.7754762 0.9987369
#>  [3,]    500   0.9937948   0.8059183 0.7919063 0.9943103
#>  [4,]   1000   0.9861357   0.8224325 0.8049691 0.9876265
#>  [5,]   2000   0.9720090   0.8430224 0.8214885 0.9759178
#>  [6,]   4000   0.9250541   0.8858478 0.8576031 0.9408427
#>  [7,]   8000   0.8707224   0.9165290 0.8857480 0.9051178
#>  [8,]  16000   0.7372786   0.9594746 0.9311339 0.8309098
#>  [9,]  32000   0.5936829   0.9837722 0.9645255 0.7651379
#> [10,]  54000   0.4863330   0.9928155 0.9805100 0.7222734
#> [11,] 100000   0.3470470   0.9981097 0.9927245 0.6728613