mhrr {mStats}

Calculating Risk Ratios

Description

mhrr() calculates different measures of risk including risk ratios (RR) as well as Mantel-Haenszel pooled estimates.

Usage

mhrr(
  data,
  exp,
  case,
  strata = NULL,
  exp_value = NULL,
  case_value = NULL,
  digits = 4
)

Arguments

data

data.frame

exp

exposure or independent variables

case

case or dependent variables (outcomes)

strata

if specified, MH OR is calculated.

exp_value

value for exposure as reference

case_value

value for outcome as reference

digits

specify rounding of numbers. See round.

Details

Rows and Columns can be rearranged by specifying exp_value and case_value. This is used when the exposed and case values are not at the right place in 2x2 tables.

Reference row value can be specified in exp_value.

Attributable fractions, Attr. Frac. Exp and Attr. Frac. Pop among exposed and population are calculated when RR is greated than or equal to 1. If RR is less than 1, preventable fractions, Prev. Frac. Exp and Attr. Frac. Pop are calculated.

It produces a table with Risk Ratio, 95% CI as well as p-value. If strata is specified, Mantel-Haenzsel Pooled estimates of ⁠Risk Ratio⁠ is generated along with Chi-squared test for homogeneity.

Author(s)

Email: [e-mail]

Website: https://myominnoo.github.io/

References

1. Betty R. Kirkwood, Jonathan A.C. Sterne (2006, ISBN:978–0–86542–871–3)

2. B. Burt Gerstman (2013, ISBN:978-1-4443-3608-5)

3. Douglas G Altman (2005, ISBN:0 7279 1375 1)

Examples

### Example from Essential Medical Statistics
# Page 178, Chapter 18: Controlling for confounding: Stratification
lepto <- expandtbl(
    male = c(36, 14, 50, 50), female = c(24, 126, 10, 90),
    exp_name = "area", exp_lvl = c("Rural", "Urban"),
    case_name = "ab", case_lvl = c("Yes", "No"),
    strata_name = "gender"
)

## label variables and data
lepto <- label(lepto, "Prevalence survey of leptospirosis in West Indies")
lepto <- label(lepto, area="Type of area", ab = "Leptospirosis Antibodies",
                  gender="Gener: Male or Female")

## Calculate RR
mhrr(lepto, area, ab)

## Calculate MHRR
mhrr(lepto, area, ab, gender)


## Not run: 
### Demonstration: Calculating Risk Ratios

## Essential Medical Statistics, Betty R. Kirkwood, Second Edition
## Chapter 16, Table 16.4, Page 154
## For Risk Ratio
lung <- expandtbl(
    c(39, 29961, 6, 59994),
    exp_name = "smoking",
    exp_lvl = c("Smokers", "Non-smokers"),
    case_name = "cancer",
    case_lvl = c("Yes", "No")
)

## label variable and dataset
lung <- labelVar(lung, smoking="Yes or No", cancer="Yes or no")
lung <- labelData(lung, "Follow up lung cancer study")

## check dataset
codebook(lung)

## calculate RR
mhrr(lung, smoking, cancer, exp_value = "Smokers", case_value = "Yes")



## Simpson's paradox
## Burt Gerstman's Epidemiology, page 326, table 14.1
simpson <- expandtbl("1" = c(1000, 9000, 50, 950),
                        "2" = c(95, 5, 5000, 5000),
                        exp_name = "trt",
                        exp_lvl = c("new", "standard"),
                        case_name = "case",
                        case_lvl = c("alive", "dead"),
                        strata_name = "clinic")

## calculate RR
mhrr(simpson, trt, case, exp_value = "new", case_value = "alive")

## calculate MH RR
mhrr(simpson, trt, case, clinic)


## End(Not run)