Cinelli-Hazlett sensitivity under a hypothesised confounder

Formula: adjusted estimate under hypothesised confounder R2_Y * R2_D

Usage

Cnffvw(y, D, X = NULL, R2_Y = 0, R2_D = 0, q = 1)

Arguments

y

Outcome.

D

Treatment.

X

Observed covariates, or NULL.

R2_Y

Hypothesised partial R2 with the outcome.

R2_D

Hypothesised partial R2 with the treatment.

q

Fraction of the estimate the confounder would explain.

Value

Whatever Chzlt returns.

Details

cnffvw and chzlt are the same method; this function forwards to Chzlt under its own argument names.

References

Cinelli & Hazlett (2020), Making Sense of Sensitivity, JRSS B 82(1):39-67.

Examples

V <- c(1, 2, 3, 4, 5, 6, 7, 8)
Cnffvw(V, V)
#> $estimate
#> [1] 1
#> 
#> $tau
#> [1] 1
#> 
#> $se
#> [1] 0
#> 
#> $t
#> [1] NaN
#> 
#> $df
#> [1] 6
#> 
#> $bias
#> [1] 0
#> 
#> $adjusted_se
#> [1] 0
#> 
#> $rv_q
#> [1] NaN
#> 
#> $r2_yd_x
#> [1] NaN
#> 
#> $robust
#> [1] 1
#> 
#> $n
#> [1] 8
#> 
#> $method
#> [1] "Cinelli-Hazlett omitted-variable-bias sensitivity"
#> 
#> attr(,"class")
#> [1] "morie_rich_result" "list"