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Maya Sen (Gov)
Gary King (Gov)

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26 February 2013

App Stats: Mozaffarian on "Estimating the Global Impact of Poor Dietary Habits on Chronic Diseases"

We hope you can join us this Wednesday, February 27, 2013 for the Applied Statistics Workshop. Dariush Mozaffarian, Associate Professor in the Department of Epidemiology at the Harvard School of Public Health, will give a presentation entitled "Estimating the Global Impact of Poor Dietary Habits on Chronic Diseases". A light lunch will be served at 12 pm and the talk will begin at 12.15.

"Estimating the Global Impact of Poor Dietary Habits on Chronic Diseases"
Dariush Mozaffarian
Department of Epidemiology, Harvard School of Public Health
CGIS K354 (1737 Cambridge St.)
Wednesday, February 27, 2013, 12.00pm

Abstract:

Nearly every nation in the world is undergoing rapid epidemiologic transition toward noncommunicable chronic diseases (NCDs) including cardiovascular disease (CVD), obesity, diabetes, and cancers. Numerous organizations including the United Nations, World Health Organization, US Centers for Disease Control and Prevention, and other national and international organizations have emphasized the importance of dietary habits as a key risk factor for NCDs. Yet, the burdens of suboptimal dietary habits on NCDs globally, as well as heterogeneity in these burdens by region, country, age, and sex, are not established. Quantification of these burdens has been limited by inadequate or absent data on dietary habits in many nations, not only for each country as a whole, but also for age- and sex-specific strata. As part of our work in the 2010 Global Burden of Diseases Nutrition and Chronic Diseases Group, we systematically identified and obtained data on national and subnational individual-level surveys of dietary consumption worldwide; and used a Bayesian hierarchical model to evaluate and account for differences in comparability, assessment methods, representativeness, and missingness. We also quantified effects of dietary habits on NCDs, including differences by age, in new meta-analyses. We compiled additional data to quantify the alternative optimal distribution of key dietary risk factors, and the numbers of cause-specific deaths by country, age, and sex. Using this compilation of global data, we used comparative risk assessment to quantify the impacts of current dietary habits on NCDs in each nation around the world. The case of sugar-sweetened beverages (SSBs) and CVD, adiposity-related cancers, and diabetes will be presented as an example of our newest findings.

Posted by Konstantin Kashin at 12:43 AM | Comments (1)

App Stats: Mozaffarian on "Estimating the Global Impact of Poor Dietary Habits on Chronic Diseases"

We hope you can join us this Wednesday, February 27, 2013 for the Applied Statistics Workshop. Dariush Mozaffarian, Associate Professor in the Department of Epidemiology at the Harvard School of Public Health, will give a presentation entitled "Estimating the Global Impact of Poor Dietary Habits on Chronic Diseases". A light lunch will be served at 12 pm and the talk will begin at 12.15.

"Estimating the Global Impact of Poor Dietary Habits on Chronic Diseases"
Dariush Mozaffarian
Department of Epidemiology, Harvard School of Public Health
CGIS K354 (1737 Cambridge St.)
Wednesday, February 27, 2013, 12.00pm

Abstract:

Nearly every nation in the world is undergoing rapid epidemiologic transition toward noncommunicable chronic diseases (NCDs) including cardiovascular disease (CVD), obesity, diabetes, and cancers. Numerous organizations including the United Nations, World Health Organization, US Centers for Disease Control and Prevention, and other national and international organizations have emphasized the importance of dietary habits as a key risk factor for NCDs. Yet, the burdens of suboptimal dietary habits on NCDs globally, as well as heterogeneity in these burdens by region, country, age, and sex, are not established. Quantification of these burdens has been limited by inadequate or absent data on dietary habits in many nations, not only for each country as a whole, but also for age- and sex-specific strata. As part of our work in the 2010 Global Burden of Diseases Nutrition and Chronic Diseases Group, we systematically identified and obtained data on national and subnational individual-level surveys of dietary consumption worldwide; and used a Bayesian hierarchical model to evaluate and account for differences in comparability, assessment methods, representativeness, and missingness. We also quantified effects of dietary habits on NCDs, including differences by age, in new meta-analyses. We compiled additional data to quantify the alternative optimal distribution of key dietary risk factors, and the numbers of cause-specific deaths by country, age, and sex. Using this compilation of global data, we used comparative risk assessment to quantify the impacts of current dietary habits on NCDs in each nation around the world. The case of sugar-sweetened beverages (SSBs) and CVD, adiposity-related cancers, and diabetes will be presented as an example of our newest findings.

Posted by Konstantin Kashin at 12:43 AM | Comments (1)

18 February 2013

App Stats: Garcia on "When and Why is Attrition a Problem in Randomized Controlled Experiments and How to Diagnose It"

We hope you can join us this Wednesday, February 20, 2013 for the Applied Statistics Workshop. Fernando Martel Garcia, a Research Fellow at the Harvard School of Public Health, will give a presentation entitled "When and Why is Attrition a Problem in Randomized Controlled Experiments and How to Diagnose It". A light lunch will be served at 12 pm and the talk will begin at 12.15.

"When and Why is Attrition a Problem in Randomized Controlled Experiments and How to Diagnose It"
Fernando Martel Garcia
Harvard School of Public Health
CGIS K354 (1737 Cambridge St.)
Wednesday, February 20th, 2013 12.00 pm

Abstract:

Attrition is the Achilles' Heel of the randomized experiment: it is fairly common, and it can unravel the benefits of randomization. This study considers when and why attrition is a problem, and how it can be diagnosed. The extant literature remains ambiguous because it relies on the language of probability, whereas problematic attrition depends on the underlying causal relations. This ambiguity arises because causation implies correlation but not vice versa. Using the structural causal language of directed acyclic graphs I show attrition is a problem when it is an active collider between the treatment and the outcome, or when the latent outcome is a mediator between the treatment and the attrition. Moreover, whether observed outcomes are representative of all outcomes, or only comparable across experimental arms, depends on two d-separation conditions. One of these is directly testable from the data.

Posted by Konstantin Kashin at 12:30 AM

11 February 2013

App Stats: Carpenter on "R&D Abandonment in Regulatory Equilibrium: Evidence from Asset Price Shocks Induced by FDA Decisions"

We hope you can join us this Wednesday, February 13, 2013 for the Applied Statistics Workshop. Dan Carpenter, the Allie S. Freed Professor of Government from the Department of Government at Harvard University, will give a presentation entitled "R&D Abandonment in Regulatory Equilibrium: Evidence from Asset Price Shocks Induced by FDA Decisions". A light lunch will be served at 12 pm and the talk will begin at 12.15.

"R&D Abandonment in Regulatory Equilibrium: Evidence from Asset Price Shocks Induced by FDA Decisions"
Dan Carpenter
Government Department, Harvard University
CGIS K354 (1737 Cambridge St.)
Wednesday, February 13th, 2013 12.00 pm

This is joint work with Jessica Blankshain (Harvard University) and Susan Moffitt (Brown University).

Abstract:

Observers of approval regulation regimes such as FDA drug review have long proposed that they cause private companies to avoid developing new products that would otherwise have been marketed. The welfare conclusions and policy recommendations vary, but the causal claim is common. Yet most such claims suffer from the problem of endogeneity and non-random assignment, such that the necessary counterfactual cannot be sustained. If a regulatory decision occurs and drug projects are discontinued or delayed, the analyst cannot usually infer whether it was a change in regulation or something else that caused the project abandonment. Using a rich dataset on the development of over 15,000 pharmaceutical investment projects from 1989 to 2003, we examine responses in development projects to "bad news" regulatory announcements weighted by the asset price shocks in a general equilibrium financial market. Using a Lévy process model of asset price evolution, we demonstrate that the abrupt changes in sponsor asset prices upon the announcement of adverse regulatory news are plausibly non-anticipable for all participants but the regulator. Specifically, for the development projects of companies other than the sponsor affected, they are quasi-random, conditional on all information known on the day before the announcement. This assumption is supported by analysis of data, and then used to identify a model of regulatory effects upon drug development. The results suggest robust effects of induced project abandonment by regulatory decisions; a ten percent (negative) shock to the sponsor's asset price in response to adverse FDA news is sufficient to induce a three to four percent increase in the hazard rate of drug project discontinuation for all other firms' projects in the months following the news. While some immediate responses to adverse regulatory news are witnessed, most response takes place in a six month period following the event. Effects are larger for bad news from advisory committee decisions and FDA requests for additional data, and are negative (development-facilitating) for surprise other-company abandonments where FDA factors are implicit. The results are generally supportive of dominant theoretical models of endogenous approval regulation (Carpenter and Ting 2007), but policy implications are unclear and depend upon the potential health and welfare effects of the therapies foregone.

Posted by Konstantin Kashin at 1:57 AM

4 February 2013

App Stats: Hatfield on "Statistical properties and health policy applications of microsimulation"

We hope you can join us this Wednesday, February 6, 2013 for the Applied Statistics Workshop. Laura Hatfield, an Assistant Professor from the Department of Health Care Policy at the Harvard Medical School, will give a presentation entitled "Statistical properties and health policy applications of microsimulation". A light lunch will be served at 12 pm and the talk will begin at 12.15.

"Statistical properties and health policy applications of microsimulation"
Laura Hatfield
Department of Health Care Policy, Harvard Medical School
CGIS K354 (1737 Cambridge St.)
Wednesday, September 6th, 2013 12.00 pm

Abstract:

When forecasting the impact of novel policy interventions, simulations are standard. If the behavior of the entire system is complex and not well identified by existing data, simulations that focus on the behavior of smaller units, such as individuals, may be preferred. So-called microsimulation models can incorporate complications such as clustering, nonlinearity, non-standard distributions, and time-dependence. This talk will present an overview of microsimulation techniques, with a focus on statistical features and dynamic (vs static) simulation, especially in health policy settings. I will also describe the current development of a model of health insurance coverage and health care spending of Medicare beneficiaries.

Posted by Konstantin Kashin at 1:42 AM