# dlr.regtest: Differences in Diagnostic Likelihood Ratios In DTComPair: Comparison of Binary Diagnostic Tests in a Paired Study Design

## Description

Performs a test for differences in (positive and negative) diagnostic likelihood ratios (DLRs) of two binary diagnostic tests in a paired study using a regression model approach proposed by Gu and Pepe (2009).

## Usage

 `1` ```dlr.regtest(tab, alpha) ```

## Arguments

 `tab` An object of class `tab.paired`. `alpha` Significance level alpha for 100(1-alpha)%-confidence intervals, the default is 0.05.

## Details

The null hypothesis rDLR = DLR of Test 1 / DLR of Test 2 = 1 is tested with respect to both positive and negative DLRs of the two diagnostic tests.

This function calls `DLR`, a general implementation of the method proposed by Gu and Pepe (2009).

## Value

A list containing

 `pdlr` A list with `test1` (the positive DLR of test 1), `test2` (the positive DLR of test 2), `ratio` (the ratio of positive DLRs, computed as `test1/test2`, `se.log` (the standard error of the logarithm of `ratio`), the `test.statistic` and the corresponding `p.value`. `ndlr` A list with `test1` (the negative DLR of test 1), `test2` (the negative DLR of test 2), `ratio` (the ratio of negative DLRs, computed as `test1/test2`, `se.log` (the standard error of the logarithm of `ratio`), the `test.statistic` and the corresponding `p.value`. `alpha` The significance level alpha used to compute 100(1-alpha)%-confidence intervals for the `ratio` of positive and negative DLRs, the default is 0.05. `method` The name of the method used to compare the positive and negative DLRs, here “diagnostic likelihood regression model (regtest)”.

## References

Gu, W. and Pepe, M. S. (2009). Estimating the capacity for improvement in risk prediction with a marker. Biostatistics, 10(1):172-86.

`DLR`

## Examples

 ```1 2 3 4 5 6``` ```data(Paired1) # Hypothetical study data ptab <- tab.paired(d=d, y1=y1, y2=y2, data=Paired1) ptab dlr.results <- dlr.regtest(ptab) str(dlr.results) dlr.results ```

### Example output

```Loading required package: gee
Two binary diagnostic tests (paired design)

Test1: 'y1'
Test2: 'y2'

Diseased:
Test1 pos. Test1 neg. Total
Test2 pos.        319         22   341
Test2 neg.         78         32   110
Total             397         54   451

Non-diseased:
Test1 pos. Test1 neg. Total
Test2 pos.         31         22    53
Test2 neg.         53        155   208
Total              84        177   261

List of 4
\$ pdlr  :List of 8
..\$ test1         : num 2.74
..\$ test2         : num 3.72
..\$ ratio         : num 0.735
..\$ se.log        : num 0.133
..\$ test.statistic: num -2.33
..\$ p.value       : num 0.02
..\$ lcl           : num 0.566
..\$ ucl           : num 0.953
\$ ndlr  :List of 8
..\$ test1         : num 0.177
..\$ test2         : num 0.306
..\$ ratio         : num 0.577
..\$ se.log        : num 0.137
..\$ test.statistic: num -4
..\$ p.value       : num 6.22e-05
..\$ lcl           : num 0.441
..\$ ucl           : num 0.755
\$ alpha : num 0.05
\$ method: chr "DLR regression model (regtest)"
\$pdlr
\$pdlr\$test1
[1] 2.735112

\$pdlr\$test2
[1] 3.723424

\$pdlr\$ratio
[1] 0.7345692

\$pdlr\$se.log
[1] 0.1326086

\$pdlr\$test.statistic
[1] -2.326177

\$pdlr\$p.value
[1] 0.0200091

\$pdlr\$lcl
[1] 0.5664428

\$pdlr\$ucl
[1] 0.9525973

\$ndlr
\$ndlr\$test1
[1] 0.1765568

\$ndlr\$test2
[1] 0.3060507

\$ndlr\$ratio
[1] 0.5768875

\$ndlr\$se.log
[1] 0.137376

\$ndlr\$test.statistic
[1] -4.004396

\$ndlr\$p.value
[1] 6.217627e-05

\$ndlr\$lcl
[1] 0.4407136

\$ndlr\$ucl
[1] 0.7551371

\$alpha
[1] 0.05

\$method
[1] "DLR regression model (regtest)"
```

DTComPair documentation built on May 2, 2019, 6:53 a.m.