Abstract
In some two-arm randomized trials, some participants receive the treatment assigned to the other arm as a result of technical problems, refusal of a treatment invitation, or a choice of treatment in an encouragement design. In some before-and-after studies, the availability of a new treatment changes from one time period to this next. Under assumptions that are often reasonable, the latent class instrumental variable (IV) method estimates the effect of treatment received in the aforementioned scenarios involving all-or-none compliance and all-or-none availability. Key aspects are four initial latent classes (sometimes called principal strata) based on treatment received if in each randomization group or time period, the exclusion restriction assumption (in which randomization group or time period is an instrumental variable), the monotonicity assumption (which drops an implausible latent class from the analysis), and the estimated effect of receiving treatment in one latent class (sometimes called efficacy, the local average treatment effect, or the complier average causal effect). Since its independent formulations in the biostatistics and econometrics literatures, the latent class IV method (which has no well-established name) has gained increasing popularity. We review the latent class IV method from a clinical and biostatistical perspective, focusing on underlying assumptions, methodological extensions, and applications in our fields of obstetrics and cancer research.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 147-160 |
| Number of pages | 14 |
| Journal | Statistics in Medicine |
| Volume | 35 |
| Issue number | 1 |
| DOIs | |
| State | Published - Jan 15 2016 |
Fingerprint
Keywords
- All-or-none compliance
- Causal inference
- Encouragement design, observational
- Paired availability design
- Principal stratification, randomized trial
ASJC Scopus subject areas
- Epidemiology
- Statistics and Probability
Cite this
Latent class instrumental variables : A clinical and biostatistical perspective. / Baker, Stuart G.; Kramer, Barnett S.; Lindeman, Karen Sue.
In: Statistics in Medicine, Vol. 35, No. 1, 15.01.2016, p. 147-160.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Latent class instrumental variables
T2 - A clinical and biostatistical perspective
AU - Baker, Stuart G.
AU - Kramer, Barnett S.
AU - Lindeman, Karen Sue
PY - 2016/1/15
Y1 - 2016/1/15
N2 - In some two-arm randomized trials, some participants receive the treatment assigned to the other arm as a result of technical problems, refusal of a treatment invitation, or a choice of treatment in an encouragement design. In some before-and-after studies, the availability of a new treatment changes from one time period to this next. Under assumptions that are often reasonable, the latent class instrumental variable (IV) method estimates the effect of treatment received in the aforementioned scenarios involving all-or-none compliance and all-or-none availability. Key aspects are four initial latent classes (sometimes called principal strata) based on treatment received if in each randomization group or time period, the exclusion restriction assumption (in which randomization group or time period is an instrumental variable), the monotonicity assumption (which drops an implausible latent class from the analysis), and the estimated effect of receiving treatment in one latent class (sometimes called efficacy, the local average treatment effect, or the complier average causal effect). Since its independent formulations in the biostatistics and econometrics literatures, the latent class IV method (which has no well-established name) has gained increasing popularity. We review the latent class IV method from a clinical and biostatistical perspective, focusing on underlying assumptions, methodological extensions, and applications in our fields of obstetrics and cancer research.
AB - In some two-arm randomized trials, some participants receive the treatment assigned to the other arm as a result of technical problems, refusal of a treatment invitation, or a choice of treatment in an encouragement design. In some before-and-after studies, the availability of a new treatment changes from one time period to this next. Under assumptions that are often reasonable, the latent class instrumental variable (IV) method estimates the effect of treatment received in the aforementioned scenarios involving all-or-none compliance and all-or-none availability. Key aspects are four initial latent classes (sometimes called principal strata) based on treatment received if in each randomization group or time period, the exclusion restriction assumption (in which randomization group or time period is an instrumental variable), the monotonicity assumption (which drops an implausible latent class from the analysis), and the estimated effect of receiving treatment in one latent class (sometimes called efficacy, the local average treatment effect, or the complier average causal effect). Since its independent formulations in the biostatistics and econometrics literatures, the latent class IV method (which has no well-established name) has gained increasing popularity. We review the latent class IV method from a clinical and biostatistical perspective, focusing on underlying assumptions, methodological extensions, and applications in our fields of obstetrics and cancer research.
KW - All-or-none compliance
KW - Causal inference
KW - Encouragement design, observational
KW - Paired availability design
KW - Principal stratification, randomized trial
UR - http://www.scopus.com/inward/record.url?scp=84954384808&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84954384808&partnerID=8YFLogxK
U2 - 10.1002/sim.6612
DO - 10.1002/sim.6612
M3 - Article
C2 - 26239275
AN - SCOPUS:84954384808
VL - 35
SP - 147
EP - 160
JO - Statistics in Medicine
JF - Statistics in Medicine
SN - 0277-6715
IS - 1
ER -