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Dunn G, Emsley R, Liu H, et al. Evaluation and validation of social and psychological markers in randomised trials of complex interventions in mental health: a methodological research programme. Southampton (UK): NIHR Journals Library; 2015 Nov. (Health Technology Assessment, No. 19.93.)

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Evaluation and validation of social and psychological markers in randomised trials of complex interventions in mental health: a methodological research programme.

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References

1.
MRC. Developing and Evaluating Complex Interventions: New Guidance. 2008. URL: www​.mrc.ac.uk/complexinterventionsguidance (accessed 3 June 2015).
2.
Buyse M. Towards validation of statistically reliable biomarkers. Eur J Cancer 2007;5:89–95. 10.1016/S1359-6349(07)70028-9. [CrossRef]
3.
Joffe MM, Greene T. Related causal frameworks for surrogate outcomes. Biometrics 2009;65:530–8. 10.1111/j.1541-0420.2008.01106.x. [PubMed: 18759836] [CrossRef]
4.
Beck A, Ward C, Mendelson M, Mock J, Erbaugh J. An inventory for measuring depression. Arch Gen Psychiatry 1961;4:561–71. 10.1001/archpsyc.1961.01710120031004. [PubMed: 13688369] [CrossRef]
5.
Pearl J. Causality. 2nd edn. New York, NY; Cambridge University Press; 2009. 10.1017/CBO9780511803161. [CrossRef]
6.
Rubin DB. Estimating causal effects of treatment in randomized and non-randomized studies. J Educ Psychol 1974;66:688–701. 10.1037/h0037350. [CrossRef]
7.
Angrist JD, Imbens GW, Rubin DB. Identification of causal effects using instrumental variables. J Am Stat Assoc 1996;91:444–55. 10.1080/01621459.1996.10476902. [CrossRef]
8.
Barnard J, Frangakis CE, Hill JL, Rubin DB. Principal stratification approach to broken randomized experiments: a case study of school choice vouchers in New York City. J Am Stat Assoc 2003;98:299–311. 10.1198/016214503000071. [CrossRef]
9.
Manski CF. Nonparametric bounds on treatment effects. Am Econ Rev 1990;80:319–23.
10.
Balke A, Pearl J. Bounds on treatment effects from studies with imperfect compliance. J Am Stat Assoc 1997;92:1172–6. 10.1080/01621459.1997.10474074. [CrossRef]
11.
Frangakis CE, Rubin DB. Principal stratification in causal inference. Biometrics 2002;58:21–9. 10.1111/j.0006-341X.2002.00021.x. [PMC free article: PMC4137767] [PubMed: 11890317] [CrossRef]
12.
Freeman D, Dunn G, Startup H, Kingdon D. The effects of reducing worry in patients with persecutory delusions: study protocol for a randomized controlled trial. Trials 2012;13:223. 10.1186/1745-6215-13-223. [PMC free article: PMC3551833] [PubMed: 23171601] [CrossRef]
13.
Dunn G, Fowler D, Rollinson R, Freeman D, Kuipers E, Smith B, et al. Effective elements of cognitive behaviour therapy for psychosis: results of a novel type of subgroup analysis based on principal stratification. Psychol Med 2012;42:1057–68. 10.1017/S0033291711001954. [PMC free article: PMC3315767] [PubMed: 21939591] [CrossRef]
14.
Dunn G, Bentall R. Modelling treatment-effect heterogeneity in randomized controlled trials of complex interventions (psychological treatments). Stat Med 2007;26:4719–45. 10.1002/sim.2891. [PubMed: 17476649] [CrossRef]
15.
Simon R. Clinical trials for predictive medicine: new challenges and paradigms. Clin Trials 2010;7:516–24. 10.1177/1740774510366454. [PMC free article: PMC4041069] [PubMed: 20338899] [CrossRef]
16.
Baron RM, Kenny DA. The moderator–mediator variable distinction in social psychological research: conceptual, strategic, and statistical considerations. J Pers Soc Psychol 1986;51:1173–82. 10.1037/0022-3514.51.6.1173. [PubMed: 3806354] [CrossRef]
17.
Kraemer HC, Fairburn CG, Agras WS. Mediators and moderators of treatment effects in randomized clinical trials. Arch Gen Psychiatry 2002;59:877–83. 10.1001/archpsyc.59.10.877. [PubMed: 12365874] [CrossRef]
18.
Judd CM, Kenny DA. Process analysis – estimating mediation in treatment evaluations. Eval Rev 1981;5:602–19. 10.1177/0193841X8100500502. [CrossRef]
19.
MacKinnon DP. Introduction to Statistical Mediation Analysis. New York, NY: Taylor & Francis Group; 2008.
20.
Birchwood M, Peters E, Tarrier N, Dunn G, Lewis S, Wykes T, et al. A multi-centre, randomised controlled trial of cognitive therapy to prevent harmful compliance with command hallucinations. BMC Psychiatry 2011;11:155. 10.1186/1471-244X-11-155. [PMC free article: PMC3191332] [PubMed: 21961763] [CrossRef]
21.
Barrowclough C, Haddock G, Wykes T, Beardmore R, Conrod P, Craig T, et al. Integrated motivational interviewing and cognitive behavioural therapy for people with psychosis and comorbid substance misuse: randomised controlled trial. BMJ 2010;341:c6325. 10.1136/bmj.c6325. [PMC free article: PMC2991241] [PubMed: 21106618] [CrossRef]
22.
Gallop R, Small DS, Lin JY, Elliot MR, Joffe MM, Ten Have TR. Mediation analysis with principal stratification. Stat Med 2009;28:1108–30. 10.1002/sim.3533. [PMC free article: PMC2669107] [PubMed: 19184975] [CrossRef]
23.
Green J, Charman T, McConachie H, Aldred C, Slonims V, Howlin H, et al. Parent-mediated communication-focused treatment in children with autism (PACT): a randomised controlled trial. Lancet 2010;375:2152–60. 10.1016/S0140-6736(10)60587-9. [PMC free article: PMC2890859] [PubMed: 20494434] [CrossRef]
24.
Bruce ML, Ten Have TR, Reynolds CF, Katz II, Schulberg HC, Mulsant BH, et al. Reducing suicidal ideation and depressive symptoms in depressed older primary care patients – a randomized controlled trial. JAMA 2004;291:1081–91. 10.1001/jama.291.9.1081. [PubMed: 14996777] [CrossRef]
25.
Ten Have TR, Joffe MM, Lynch KG, Brown GK, Maisto SA, Beck AT. Causal mediation analysis with rank preserving models. Biometrics 2007;63:926–34. 10.1111/j.1541-0420.2007.00766.x. [PubMed: 17825022] [CrossRef]
26.
Bellamy SL, Lin JY, Ten Have TR. An introduction to causal modelling in clinical trials. Clin Trials 2007;4:58–73. 10.1177/1740774506075549. [PubMed: 17327246] [CrossRef]
27.
Lynch K, Cary M, Gallop R, Ten Have TR. Causal mediation analyses for randomized trials. Health Serv Outcomes Res Methodol 2008;8:57–76. 10.1007/s10742-008-0028-9. [PMC free article: PMC2688317] [PubMed: 19484136] [CrossRef]
28.
Lord C, Risi S, Lambrecht L, Cook EH Jr, Leventhal BL, DiLavore PC, et al. The autism diagnostic observation schedule-generic: a standard measure of social and communication deficits associated with the spectrum of autism. J Autism Dev Disord 2000;30:205–23. 10.1023/A:1005592401947. [PubMed: 11055457] [CrossRef]
29.
MacKinnon DP, Dwyer JH. Estimating mediated effects in prevention studies. Eval Rev 1993;17:144–58. 10.1177/0193841X9301700202. [CrossRef]
30.
Emsley R, Dunn G, White IR. Mediation and moderation of treatment effects in randomised controlled trials of complex interventions. Stat Methods Med Res 2010;19:237–70. 10.1177/0962280209105014. [PubMed: 19608601] [CrossRef]
31.
Emsley R, Dunn G. Evaluation of Potential Mediators in Randomized Trials of Complex Interventions (Psychotherapies). In Berzuini C, Dawid P, Bernardinelli L, editors. Causality: Statistical Perspectives and Applications. Chichester: Wiley; 2012. pp. 290–309. 10.1002/9781119945710.ch20. [CrossRef]
32.
Robins JM, Greenland S. Identifiability and exchangeability for direct and indirect effects. Epidemiology 1992;3:143–55. 10.1097/00001648-199203000-00013. [PubMed: 1576220] [CrossRef]
33.
Pearl J. Direct and Indirect Effects. In Breese J, Koller D, editors. Proceedings of the Seventeenth Conference on Uncertainty in Artificial Intelligence. San Francisco, CA: Morgan Kaufmann; 2011. pp. 411–20.
34.
Cai ZH, Kuroki M, Pearl J, Tian J. Bounds on direct effects in the presence of confounded intermediate variables. Biometrics 2008;64:695–701. 10.1111/j.1541-0420.2007.00949.x. [PubMed: 18162106] [CrossRef]
35.
Wooldridge JM. Econometric Analysis of Cross Section and Panel Data. Cambridge, MA: MIT Press; 2002.
36.
VanderWeele TJ, Vansteelandt S. Conceptual issues concerning mediation, interventions and composition. Stat Interface 2009;2:457–68. 10.4310/SII.2009.v2.n4.a7. [CrossRef]
37.
VanderWeele TJ, Vansteelandt S. Odds ratios for mediation analysis for a dichotomous outcome. Am J Epidemiol 2010;172:1339–48. 10.1093/aje/kwq332. [PMC free article: PMC2998205] [PubMed: 21036955] [CrossRef]
38.
Emsley R, Liu H, Dunn G, Valeri L, VanderWeele TJ. Paramed: a command to perform causal mediation analysis using parametric models. 2015; in preparation.
39.
Herting JR. Evaluating and rejecting true mediation models: a cautionary note. Prevent Sci 2002;3:285–9. 10.1023/A:1020828709115. [PubMed: 12458766] [CrossRef]
40.
Holland PW. Causal inference, path analysis and recursive structural equation models (with discussion). Sociol Methodol 1988;18:449–84. 10.2307/271055. [CrossRef]
41.
Kaufman JS, MacLehose R, Kaufman S. A further critique of the analytic strategy of adjusting for covariates to identify biologic mediation. Epidemiol Perspect Innovations 2004;1. [PMC free article: PMC526390] [PubMed: 15507130]
42.
Kaufman S, Kaufman JS, MacLehose RF, Greenland S, Poole C. Improved estimation of controlled direct effects in the presence of unmeasured confounding of intermediate variables. Stat Med 2005;24:1683–702. 10.1002/sim.2057. [PubMed: 15742358] [CrossRef]
43.
Tritchler D. Explanatory analyses of randomised studies. Biometrics 1996;52:1450–6. 10.2307/2532858. [PubMed: 8962463] [CrossRef]
44.
Tritchler D. Reasoning about data with directed graphs. Stat Med 1999;18:2067–76. 10.1002/(SICI)1097-0258(19990830)18:16<2067::AID-SIM182>3.0.CO;2-2. [PubMed: 10441763] [CrossRef]
45.
McDonald RP. Haldane’s lungs: a case study in path analysis. Mul Behav Res 1997;32:1–38. 10.1207/s15327906mbr3201_1. [PubMed: 26751104] [CrossRef]
46.
Wooldridge JM. Introductory Econometrics: A Modern Approach. 2nd edn. Ohio, OH: Thompson Learning; 2003.
47.
Gennetian LA, Morris PA, Bos JM, Bloom HS. Constructing Instrumental Variables From Experimental Data to Explore how Treatments Produce Effects. In Bloom HS, editor. Learning More From Social Experiments: Evolving Analytic Approaches. 1st edn. New York, NY: Russell Sage Foundation; 2005. pp. 75–114.
48.
Gennetian LA, Magnuson K, Morris PA. From statistical associations to causation: what developmentalists can learn from instrumental variables techniques coupled with experimental data. Develop Psychol 2008;44:381–94. 10.1037/0012-1649.44.2.381. [PMC free article: PMC3208329] [PubMed: 18331130] [CrossRef]
49.
Sobel ME. Identification of causal parameters in randomised studies with mediating variables. J Educ Behav Stat 2008;33:230–51. 10.3102/1076998607307239. [CrossRef]
50.
Fischer-Lapp K, Goetghebeur E. Practical properties of some structural mean analyses of the effect of compliance in randomized trials. Control Clin Trials 1999;20:531–46. 10.1016/S0197-2456(99)00027-6. [PubMed: 10588294] [CrossRef]
51.
Albert JM. Mediation analysis via potential outcomes models. Stat Med 2008;27:1282–304. 10.1002/sim.3016. [PubMed: 17691077] [CrossRef]
52.
Ten Have TR, Joffe M. A review of causal estimation of effects in mediation analyses. Stat Methods Med Res 2012;21:77–107. 10.1177/0962280210391076. [PubMed: 21163849] [CrossRef]
53.
Fuller WA. Measurement Error Models. New York, NY: Wiley; 1987. 10.1002/9780470316665. [CrossRef]
54.
Carroll RJ, Ruppert D, Stefanski LA, Crainiceanu CM. Measurement Error in Non-Linear Models. 2nd edn. London: Chapman & Hall; 2006. 10.1201/9781420010138. [CrossRef]
55.
Bollen K. Structural Equations with Latent Variables. 2nd edn. New York, NY: John Wiley & Sons, Inc; 1989. 10.1002/9781118619179. [CrossRef]
56.
Dunn G. Statistical Evaluation of Measurement Errors. 2nd edn. London: Arnold; 2004.
57.
Dunn G. Regression models for method comparison data. J Biopharm Stat 2007;17:739–56. 10.1080/10543400701329513. [PubMed: 17613651] [CrossRef]
58.
Dunn G. The problem of measurement error in modelling the effect of compliance in a randomised trial. Stat Med 1999;18:2863–77. 10.1002/(SICI)1097-0258(19991115)18:21<2863::AID-SIM238>3.0.CO;2-I. [PubMed: 10523747] [CrossRef]
59.
Goetghebeur E, Vansteelandt S. Structural mean models for compliance analysis in randomised clinical trials and the impact of errors in exposure. Stat Methods Med Res 2005;14:397–415. 10.1191/0962280205sm407oa. [PubMed: 16178139] [CrossRef]
60.
Dunn G, Everitt BS, Pickles A. Modelling Covariances and Latent Variables in EQS. London: Chapman & Hall; 1993.
61.
Weir CJ, Walley RJ. Statistical evaluation of biomarkers as surrogate endpoints: literature review. Stat Med 2006;25:183–203. 10.1002/sim.2319. [PubMed: 16252272] [CrossRef]
62.
Daniels MJ, Hughes MD. Meta-analysis for the evaluation of potential surrogate markers. Stat Med 1997;16:1965–82. 10.1002/(SICI)1097-0258(19970915)16:17<1965::AID-SIM630>3.0.CO;2-M. [PubMed: 9304767] [CrossRef]
63.
Burzykowski T, Molenberghs G, Buyse M. The Evaluation of Surrogate Endpoints. New York, NY: Springer; 2006.
64.
Florens JP, Heckman JJ, Meghir C, Vytlacil E. Identification of treatment effects using control functions in models with continuous, endogenous treatment and heterogeneous effects. Econometrica 2008;76:1191–206. 10.3982/ECTA5317. [CrossRef]
65.
Emsley RA, Dunn G, Liu H, Clarke P, White IR, Windmeijer F. Estimating rank preserving models using instrumental variables for causal mediation analysis. 2015; in preparation.
66.
Hamilton M. A rating scale for depression. J Neurol Neurosurg Psychiatry 1960;23:56–62. 10.1136/jnnp.23.1.56. [PMC free article: PMC495331] [PubMed: 14399272] [CrossRef]
67.
Beck AT, Brown GK, Steer RA. Psychometric characteristics of the scale for suicide ideation with psychiatric outpatients. Behav Res Ther 1997;35:1039–46. 10.1016/S0005-7967(97)00073-9. [PubMed: 9431735] [CrossRef]
68.
Follmann D. Augmented designs to assess immune response in vaccine trials. Biometrics 2006;62:1161–9. 10.1111/j.1541-0420.2006.00569.x. [PMC free article: PMC2536776] [PubMed: 17156291] [CrossRef]
69.
Gunderson JG, Frank AF, Katz HM, Vannicelli ML, Frosch JP, Knapp PH. Effects of psychotherapy in schizophrenia: II. Comparative outcome of two forms of treatment. Schizophr Bull 1984;10:564–98. 10.1093/schbul/10.4.564. [PubMed: 6151246] [CrossRef]
70.
Jo B. Estimation of intervention effects with noncompliance: alternative model specifications. J Educ Behav Stat 2002;27:385–409. 10.3102/10769986027004385. [CrossRef]
71.
Dunn G, Maracy M, Tomenson B. Estimating treatment effects from randomized clinical trials with noncompliance and loss to follow-up: the role of instrumental variable methods. Stat Method Med Res 2005;14:369–95. 10.1191/0962280205sm403oa. [PubMed: 16178138] [CrossRef]
72.
Dunn G, Maracy M, Dowrick C, Ayuso-Mateos JL, Dalgard OS, Page H, et al. Estimating psychological treatment effects from an RCT with both non-compliance and loss to follow-up. Br J Psychiatry 2013;183:323–31. 10.1192/bjp.183.4.323. [PubMed: 14519610] [CrossRef]
73.
Little RJA, Rubin DB. Statistical Analysis with Missing Data. 2nd edn. Hoboken, NJ: Wiley; 2002. 10.1002/9781119013563. [CrossRef]
74.
Frangakis CE, Rubin DB. Addressing complications of intention-to-treat analysis in the combined presence of all-or-none treatment-noncompliance and subsequent missing outcomes. Biometrika 1999;86:365–79. 10.1093/biomet/86.2.365. [CrossRef]
75.
Lewis S, Tarrier N, Haddock G, Bentall R, Kinderman P, Kingdon D, et al. Randomised controlled trial of cognitive–behavioural therapy in early schizophrenia: acute-phase outcomes. Br J Psychiatry 2002;181:S91–7. 10.1192/bjp.181.43.s91. [PubMed: 12271807] [CrossRef]
76.
Tarrier N, Lewis S, Haddock G, Bentall R, Drake R, Kinderman P, et al. Cognitive–behavioural therapy in first-episode and early schizophrenia – 18-month follow-up of a randomised controlled trial. Br J Psychiatry 2004;184:231–9. 10.1192/bjp.184.3.231. [PubMed: 14990521] [CrossRef]
77.
Kay SR, Fiszbein A, Opler LA. The positive and negative syndrome scale (PANSS) for schizophrenia. Schiz Bull 1987;13:261–76. 10.1093/schbul/13.2.261. [PubMed: 3616518] [CrossRef]
78.
Efron B, Tibshirani RJ. An Introduction to the Bootstrap. London: Chapman & Hall; 1993.
79.
Muthén LK, Muthén BO. Mplus User’s Guide. Los Angeles, CA: Muthén & Muthén; 1998–2012.
80.
Pickles A, Green J and the PACT consortium. Therapeutic mechanism in the MRC Pre-school Autism Communication Trial: implications for study design and parent focussed therapy for children. J Child Psychol Psychiatry 2015;56:162–70. 10.1111/jcpp.12291. [PubMed: 25039961] [CrossRef]
81.
Garety P, Fowler D, Freeman D, Bebbington P, Dunn G, Kuipers E. Cognitive–behavioural therapy and family intervention for relapse prevention and symptom reduction in psychosis: randomised controlled trial. Br J Psychiatry 2008;192:412–23. 10.1192/bjp.bp.107.043570. [PubMed: 18515890] [CrossRef]
82.
Cheong J, MacKinnon D, Khoo ST. Investigation of mediational processes using parallel process latent growth curve modeling. Struct Equation Modeling 2003;10:238. 10.1207/S15328007SEM1002_5. [PMC free article: PMC2821108] [PubMed: 20157639] [CrossRef]
83.
Muthén B, Khoo ST. Longitudinal studies of achievement growth using latent variable modeling. Learn Individ Differences 1998;10:73–101. 10.1016/S1041-6080(99)80135-6. [CrossRef]
84.
McArdle JJ. Latent variable modeling of differences and changes with longitudinal data. Ann Rev Psychol 2009;60:577–605. 10.1146/annurev.psych.60.110707.163612. [PubMed: 18817479] [CrossRef]
85.
Muthén B, Brown H. Estimating drug effects in the presence of placebo response: Causal inference using growth mixture modeling. Stat Med 2009;28:3363–85. 10.1002/sim.3721. [PMC free article: PMC2818509] [PubMed: 19731223] [CrossRef]
86.
Asparouhov T, Muthén B. Auxiliary variables in mixture modeling: 3-Step approaches using Mplus. Mplus Web Notes: No. 15 Version 8, 5 August 2014.
87.
Bullock JG, Green DP, Ha SE. Yes, but what’s the mechanism? (Don’t expect an easy answer). J Personality Soc Psychol 2010;98:550–8. 10.1037/a0018933. [PubMed: 20307128] [CrossRef]
88.
Burgess S, Thompson SG. Avoiding bias from weak instruments in Mendelian randomisation studies. Int J Epidemiol 2011;40:755–64. 10.1093/ije/dyr036. [PubMed: 21414999] [CrossRef]
89.
Burgess S, Thompson SG. Bias in causal estimates from Mendelian randomisation studies with weak instruments. Stat Med 2011;30:1312–23. 10.1002/sim.4197. [PubMed: 21432888] [CrossRef]
90.
Davey Smith G, Ebrahim S. ‘Mendelian randomisation’: can genetic epidemiology contribute to understanding environmental determinants of disease? Int J Epidemiology 2003;32:1–22. 10.1093/ije/dyg070. [PubMed: 12689998] [CrossRef]
91.
Lawlor DA, Harbord RM, Sterne JAC, Timpson N, Davey Smith G. Mendelian randomisation: using genes as instruments for making causal inferences in epidemiology. Stat Med 2008;27:1133–63. 10.1002/sim.3034. [PubMed: 17886233] [CrossRef]
92.
Didelez V, Sheehan NA. Mendeleian randomisation as an instrumental variable approach to causal inference. Stat Methods Med Res 2007;16:309–30. 10.1177/0962280206077743. [PubMed: 17715159] [CrossRef]
93.
Garety PA, Kuipers E, Fowler D, Freeman D, Bebbington PE. A cognitive model of the positive symptoms of psychosis. Psychol Med 2001;31:189–95. 10.1017/S0033291701003312. [PubMed: 11232907] [CrossRef]
94.
Garety P, Freeman D. Cognitive approaches to delusions: a critical review of theories and evidence. Br J Clin Psychol 1999;38:113–54. 10.1348/014466599162700. [PubMed: 10389596] [CrossRef]
95.
Freeman D. Suspicious minds: the psychology of persecutory delusions. Clin Psychol Rev 2007;27:425–57. 10.1016/j.cpr.2006.10.004. [PubMed: 17258852] [CrossRef]
96.
Emsley RA, VanderWeele TJ. Mediation and sensitivity analysis using two or more trials. 2015; in preparation.
97.
VanderWeele TJ. Explanation in Causal Analysis: Methods for Mediation and Interaction. New York, NY: Oxford University Press; 2015.
98.
Spencer SJ, Zanna MP, Fong GT. Establishing a causal chain: why experiments are often more effective than mediational analyses in examining psychological processes. J Pers Soc Psychol 2005;89:845–51. 10.1037/0022-3514.89.6.845. [PubMed: 16393019] [CrossRef]
99.
Stone-Romero EF, Rosopa PJ. The relative validity of inferences about mediation as a function of research design characteristics. Org Res Methods 2008;11:326–52. 10.1177/1094428107300342. [CrossRef]
100.
Young KY, Laird A, Zhou ZX. The efficiency of clinical trial designs for predictive biomarker validation. Clin Trials 2010;7:557–66. 10.1177/1740774510370497. [PubMed: 20571132] [CrossRef]
101.
Freidlin B, McShane LM, Korn EL. Randomized clinical trials with biomarkers: design issues. J Nat Cancer Inst 2010;102:152–60. 10.1093/jnci/djp477. [PMC free article: PMC2911042] [PubMed: 20075367] [CrossRef]
102.
Dunn G, Emsley R, Liu H, Landau S. Integrating biomarker information within trials to evaluate treatment mechanisms and efficacy for personalised medicine. Clin Trials 2013;10:712–22. 10.1177/1740774513499651. [PubMed: 24000376] [CrossRef]
103.
Imai K, Tingley D, Yamamoto T. Experimental designs for identifying causal mechanisms. J R Stat Soc A 2013;76:5–51. 10.1111/j.1467-985X.2012.01032.x. [CrossRef]
104.
Imai K, Keele L, Tingley, D, Yamamoto T. Unpacking the black box of causality: learning about causal mechanisms from experimental and observational studies. Am Political Sci Rev 2011;105:765–89. 10.1017/S0003055411000414. [CrossRef]
105.
Daniel RM, De Stavola BL, Cousens SN, Vansteelandt S. Causal mediation analysis with multiple mediators. Biometrics 2015;71:1–14. [PMC free article: PMC4402024] [PubMed: 25351114]
106.
Valeri L, Lin X, VanderWeele TJ. Mediation analysis when a continuous mediator is measured with error and the outcome follows a generalized linear model. Stat Med 2014;33:4875–90. 10.1002/sim.6295. [PMC free article: PMC4224977] [PubMed: 25220625] [CrossRef]
107.
VanderWeele TJ. Causal mediation analysis with survival data. Epidemiology 2011;22:582–5. 10.1097/EDE.0b013e31821db37e. [PMC free article: PMC3109321] [PubMed: 21642779] [CrossRef]
108.
VanderWeele TJ. Bias formulas for sensitivity analysis for direct and indirect effects. Epidemiology 2010;21:540–51. 10.1097/EDE.0b013e3181df191c. [PMC free article: PMC4231822] [PubMed: 20479643] [CrossRef]
109.
VanderWeele TJ, Arah OA. Bias formulas for sensitivity analysis of unmeasured confounding for general outcomes, treatments, and confounders. Epidemiology 2011;22:42–52. 10.1097/EDE.0b013e3181f74493. [PMC free article: PMC3073860] [PubMed: 21052008] [CrossRef]
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