by Alan
The December 2008 issue of Psychological Methods includes an article by Joseph Schafer and Joseph Kang, entitled, "Average Causal Effects From Nonrandomized Studies: A Practical Guide and Simulated Example" (abstract).
The article addresses the seemingly age-old issue of how best to approximate a causal inference when participants' levels of the purported "causal" variable have not been assigned at random. Although the article contains a fair amount of jargon and technical formulas, the key foundation appears to boil down to the following quote:
In a typical observational study... it is unlikely that [treatment condition] will be independent of [individuals' outcome scores]. The treatments may have been selected by the individuals themselves, for reasons that are possibly related to the outcomes. With observational data, a good estimate of the [average causal effect] will make use of the covariates... to help account for this dependence (p. 281).
Via a large simulation study, Schafer and Kang compare nine different approaches for covariate-based adjustment, including analysis of covariance (ANCOVA), regression, matching, propensity scores, and weighting schemes. Near the end of the article, the authors present a section entitled "Lessons Learned," containing practical recommendations.
As social-science research articles continue to use increasingly sophisticated statistical and analytical methods, Schafer and Kang's article should be a useful resource for researchers looking to remain current with state-of-the-art approaches.
Sunday, December 28, 2008
Sunday, December 21, 2008
Do Vitamin Supplements Prevent Disease?
by Alan
Today's Los Angeles Times has an article on the failure of several recent randomized clinical trials to show benefits of taking vitamin supplements for disease prevention. The article provides some good explanation for the layperson on the differences between experimental (i.e., RCT) and observational (i.e., correlational) studies for being able to make causal inferences, in my view. It also discusses some problems, specific to vitamin research, that complicate the interpretation of experimental/RCT studies, even though they're designed to hold extraneous factors constant.
First, here are some examples of the article's discussion of experimental vs. observational research:
Randomized clinical trials are designed to test one factor at a time, but vitamins and minerals consumed as part of a healthy diet work in concert with each other.
"You don't eat a food that just has beta carotene in it," said Dr. Mary L. Hardy, medical director of the Simms/Mann UCLA Center for Integrative Oncology...
Also:
"The observational studies that originally linked vitamins to better health may have been biased because people who take supplements are often healthier overall than people who don't.
"They tend to be more physically active, better educated, eat better diets, and tend not to be smokers," [the NIH's Paul] Coates said. "So you can't say for certain it's your item of interest that causes" the health benefit.
The issue that's specific to vitamin studies is as follows, focusing on the need for a "placebo" or "control" group that does not receive the treatment being tested:
For several reasons, researchers say, vitamins don't lend themselves to randomized controlled trials. Chief among them is that there is no true placebo group when it comes to vitamins and minerals, because everyone gets some in their diet."
For drugs, someone either has [the anti-impotence drug] Cialis in their system or he doesn't have Cialis," said Paul Coates, director of the NIH Office of Dietary Supplements in Bethesda, Md. But with vitamins, "there's a baseline exposure that needs to be taken into account. It makes the challenge of seeing an improvement more difficult."
My (Alan's) initial reaction to this statement was that extraneous exposure to vitamins from food consumption should not necessarily compromise researchers' ability to make a causal inference about the vitamin supplements. The experimental group would be ingesting vitamin pills plus vitamins in food, whereas the control group would be ingesting placebo (sugar) pills plus vitamins in food. Assuming the food intake to be similar in the experimental and control groups -- which is what random assignment to groups is supposed to buy us -- then the only difference between the groups should be the vitamin vs. placebo pills.
However, there's yet another complication:
A vitamin's benefit may become apparent only if people aren't getting enough of it. That could explain why vitamin D has been linked to reduced rates of heart disease, cancer and diabetes.
"Most people are vitamin-D-deficient, and that's not true for vitamin E," [the USDA's Jeffrey] Blumberg said.
Today's Los Angeles Times has an article on the failure of several recent randomized clinical trials to show benefits of taking vitamin supplements for disease prevention. The article provides some good explanation for the layperson on the differences between experimental (i.e., RCT) and observational (i.e., correlational) studies for being able to make causal inferences, in my view. It also discusses some problems, specific to vitamin research, that complicate the interpretation of experimental/RCT studies, even though they're designed to hold extraneous factors constant.
First, here are some examples of the article's discussion of experimental vs. observational research:
Randomized clinical trials are designed to test one factor at a time, but vitamins and minerals consumed as part of a healthy diet work in concert with each other.
"You don't eat a food that just has beta carotene in it," said Dr. Mary L. Hardy, medical director of the Simms/Mann UCLA Center for Integrative Oncology...
Also:
"The observational studies that originally linked vitamins to better health may have been biased because people who take supplements are often healthier overall than people who don't.
"They tend to be more physically active, better educated, eat better diets, and tend not to be smokers," [the NIH's Paul] Coates said. "So you can't say for certain it's your item of interest that causes" the health benefit.
The issue that's specific to vitamin studies is as follows, focusing on the need for a "placebo" or "control" group that does not receive the treatment being tested:
For several reasons, researchers say, vitamins don't lend themselves to randomized controlled trials. Chief among them is that there is no true placebo group when it comes to vitamins and minerals, because everyone gets some in their diet."
For drugs, someone either has [the anti-impotence drug] Cialis in their system or he doesn't have Cialis," said Paul Coates, director of the NIH Office of Dietary Supplements in Bethesda, Md. But with vitamins, "there's a baseline exposure that needs to be taken into account. It makes the challenge of seeing an improvement more difficult."
My (Alan's) initial reaction to this statement was that extraneous exposure to vitamins from food consumption should not necessarily compromise researchers' ability to make a causal inference about the vitamin supplements. The experimental group would be ingesting vitamin pills plus vitamins in food, whereas the control group would be ingesting placebo (sugar) pills plus vitamins in food. Assuming the food intake to be similar in the experimental and control groups -- which is what random assignment to groups is supposed to buy us -- then the only difference between the groups should be the vitamin vs. placebo pills.
However, there's yet another complication:
A vitamin's benefit may become apparent only if people aren't getting enough of it. That could explain why vitamin D has been linked to reduced rates of heart disease, cancer and diabetes.
"Most people are vitamin-D-deficient, and that's not true for vitamin E," [the USDA's Jeffrey] Blumberg said.
Wednesday, December 3, 2008
Call for Papers -- Edited Volume
The following Call for Papers appeared on the SEMNET (Structural Equation Modeling) discussion list:
CAUSALITY IN THE SCIENCES
A volume of papers on causality across the sciences edited by Phyllis McKayIllari, Federica Russo and Jon Williamson under contract with Oxford University Press.
http://www.kent.ac.uk/secl/philosophy/jw/2009/cits/
This book will contain original research papers that deal with causality and causal inference in the various sciences and with general questions concerning the relationship between causality, probability and mechanisms. Some chapters will be invited contributions; others will be submitted to a call for papers. All papers will be subject to a reviewing process.
TIMETABLE
1st July 2009: deadline for submission of full papers for publication to be emailed to Phyllis McKay Illari (P.McKay@kent.ac.uk) or Federica Russo (F.Russo@kent.ac.uk)
1st November 2009: notification of acceptance of papers for publication.
1st December 2009: deadline for final version of papers accepted for publication.
THE VOLUME
The volume will run to about 600 pages and will be subdivided into the following parts:
Introduction
Health Sciences
Social Sciences
Natural Sciences
Psychology and Neurosciences
Computer science and statistics
Causality, probability and mechanisms
ORGANISATION
This volume is organised by the Centre for Reasoning at the University of Kent. It is associated with the Causality in the Sciences series of conferences, and with the research project Mechanisms and Causality funded by the Leverhulme Trust.
CAUSALITY IN THE SCIENCES
A volume of papers on causality across the sciences edited by Phyllis McKayIllari, Federica Russo and Jon Williamson under contract with Oxford University Press.
http://www.kent.ac.uk/secl/philosophy/jw/2009/cits/
This book will contain original research papers that deal with causality and causal inference in the various sciences and with general questions concerning the relationship between causality, probability and mechanisms. Some chapters will be invited contributions; others will be submitted to a call for papers. All papers will be subject to a reviewing process.
TIMETABLE
1st July 2009: deadline for submission of full papers for publication to be emailed to Phyllis McKay Illari (P.McKay@kent.ac.uk) or Federica Russo (F.Russo@kent.ac.uk)
1st November 2009: notification of acceptance of papers for publication.
1st December 2009: deadline for final version of papers accepted for publication.
THE VOLUME
The volume will run to about 600 pages and will be subdivided into the following parts:
Introduction
Health Sciences
Social Sciences
Natural Sciences
Psychology and Neurosciences
Computer science and statistics
Causality, probability and mechanisms
ORGANISATION
This volume is organised by the Centre for Reasoning at the University of Kent. It is associated with the Causality in the Sciences series of conferences, and with the research project Mechanisms and Causality funded by the Leverhulme Trust.
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