evalues.OR: Compute E-value for an odds ratio and its confidence interval... In EValue: Sensitivity Analyses for Unmeasured Confounding and Other Biases in Observational Studies and Meta-Analyses

Description

Returns a data frame containing point estimates, the lower confidence limit, and the upper confidence limit on the risk ratio scale (through an approximate conversion if needed when outcome is common) as well as E-values for the point estimate and the confidence interval limit closer to the null.

Usage

 `1` ```evalues.OR(est, lo = NA, hi = NA, rare = NA, true = 1, ...) ```

Arguments

 `est` The point estimate `lo` The lower limit of the confidence interval `hi` The upper limit of the confidence interval `rare` 1 if outcome is rare (<15 percent at end of follow-up); 0 if outcome is not rare (>15 percent at end of follow-up) `true` The true OR to which to shift the observed point estimate. Typically set to 1 to consider a null true effect. `...` Arguments passed to other methods.

Examples

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29``` ```# compute E-values for OR = 0.86 with CI: [0.75, 0.99] # for a common outcome evalues.OR(0.86, 0.75, 0.99, rare = FALSE) ## Example 2 ## Hsu and Small (2013 Biometrics) Data ## sensitivity analysis after log-linear or logistic regression head(lead) ## log linear model -- obtain the conditional risk ratio lead.loglinear = glm(lead ~ ., family = binomial(link = "log"), data = lead[,-1]) est = summary(lead.loglinear)\$coef["smoking", c(1, 2)] RR = exp(est[1]) lowerRR = exp(est[1] - 1.96*est[2]) upperRR = exp(est[1] + 1.96*est[2]) evalues.RR(RR, lowerRR, upperRR) ## logistic regression -- obtain the conditional odds ratio lead.logistic = glm(lead ~ ., family = binomial(link = "logit"), data = lead[,-1]) est = summary(lead.logistic)\$coef["smoking", c(1, 2)] OR = exp(est[1]) lowerOR = exp(est[1] - 1.96*est[2]) upperOR = exp(est[1] + 1.96*est[2]) evalues.OR(OR, lowerOR, upperOR, rare=FALSE) ```

Example output

```             point     lower     upper
RR       0.9273618 0.8660254 0.9949874
E-values 1.3689529        NA 1.0761939
id smoking  lead age male edu.lt9 edu.9to11 edu.hischl edu.somecol
1 41493       1 FALSE  77    0       0         1          0           0
2 41502       1 FALSE  29    1       0         0          1           0
3 41512       1 FALSE  80    0       0         0          0           1
4 41545       1 FALSE  40    0       1         0          0           0
5 41556       1 FALSE  38    1       0         1          0           0
6 41558       1 FALSE  50    0       0         1          0           0
edu.college edu.unknown income income.mis white black mexicanam otherhispan
1           0           0   1.57          0     1     0         0           0
2           0           0   3.41          0     0     0         1           0
3           0           0   1.24          0     1     0         0           0
4           0           0   1.27          0     0     0         1           0
5           0           0   1.24          0     1     0         0           0
6           0           0   1.22          0     0     1         0           0
otherrace
1         0
2         0
3         0
4         0
5         0
6         0
Warning message:
glm.fit: algorithm did not converge
point    lower    upper
RR       2.488840 1.672007 3.704724
E-values 4.413804 2.732008       NA
Warning message:
glm.fit: algorithm did not converge
point    lower    upper
RR       1.642884 1.315436 2.051843
E-values 2.670591 1.959590       NA
```

EValue documentation built on Oct. 28, 2021, 9:10 a.m.