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calcParameters

Calculate Parameter Estimates (calcParameters)


Description

An internal function called by the tmle function to calculate the population mean effect when there is missingness in the data, but no treatment assignment. When observations are in treatment and control groups, estimates the additive treatment effect among the entire population (ATE), among the treated (ATT), and among the controls (ATC). If the outcome is binary, also the relative risk and odds ratio parameters. P-values and 95% confidence intervals are also calculated (on the log scale for RR and OR).

Usage

calcParameters(Y, A, I.Z, Delta, g1W, g0W, Q, mu1, mu0, id, family)

Arguments

Y

continuous or binary outcome variable

A

binary treatment indicator, 1 - treatment, 0 - control

I.Z

Indicator Z=z, needed for CDE estimation

Delta

indicator of missing outcome. 1 - observed, 0 - missing

g1W

censoring mechanism estimates, P(A=1|W)*P(Delta=1|A,W)

g0W

censoring mechanism estimates, P(A=0|W)*P(Delta=1|A,W)

Q

a 3-column matrix (Q(A,W), Q(1,W), Q(0,W))

mu1

targeted estimate of E(Y|A=1,W)

mu0

targeted estimate of E(Y|A=0,W)

id

subject identifier

family

family specification for regressions, generally ‘gaussian’ for continuous outcomes, ‘binomial’ for binary outcomes

Value

EY1

Population mean outcome estimate, variance, p-value, 95% confidence interval (missingness only, no treatment assignment), or NULL

ATE

additive treatment effect estimate, variance, p-value, 95% confidence interval, or NULL

RR

relative risk estimate, p-value, 95% confidence interval, log(RR), variance(log(RR)), or NULL

OR

odds ratio estimate, p-value, 95% confidence interval, log(OR), variance(log(OR)), or NULL

Author(s)

Susan Gruber

See Also


tmle

Targeted Maximum Likelihood Estimation

v1.5.0-1
BSD_3_clause + file LICENSE | GPL-2
Authors
Susan Gruber [aut, cre], Mark van der Laan [aut], Chris Kennedy [ctr]
Initial release
2020-05-20

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