mhor: Calculating Odds Ratios

In mStats: Epidemiological Data Analysis

Description

mhor() calculates odds ratios, Mantel Haenszel pooled estimates and 95% CI.

Usage

mhor(
  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 OR is greater than or equal to 1. If OR is less than 1, preventable fractions, Prev. Frac. Exp and Attr. Frac. Pop are calculated.

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

Odds Ratio, OR

OR = (D1 x H0) / (D0 x H1)

Error Factor, EF using Woolf's formula

95\% CI = OR / EF or OR x EF

EF = exp(1.96 x SE(log(OR)))

SE(log(OR)) = √{1/D1 + 1/H1 + 1/D0 + 1/H0}

Calculating p-value from Wald's z test

z = log OR / SE (log OR)

Mantel-Haenszel's OR

ORMH = Q / R

Q = ∑{(D1i x H0i) / ni}

R = ∑{(D0i x H1i) / ni}

Calculating CI for MH-OR

95\% CI = OR / EF or OR x EF

SE(ORMH) = √{V / (Q x R)}

V = ∑{(Di x Hi x n0i x n1i) / ( (ni)^2 x (ni - 1))}

Chi-square test for MHOR, df = 1

X^2 (MH), Chi-square value = U^2 / V

U = O - E

O = ∑{D1i}

E = ∑{Di x n1i / ni}

Chi-square test for Heterogeneity

X^2 = ∑{(D1i x H0i - ORMH x D0i x H1i)^2 / ORMH x Vi x ni^2}

Value

data.frame

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 OR
mhor(lepto, area, ab)

## Calculate MHOR
mhor(lepto, area, ab, gender)

mStats documentation built on Nov. 23, 2020, 9:07 a.m.