Methodology Minutes Podcasts

A podcast series produced by The Methodology Center providing information on the Center’s methods, applications, and events.

Getting Started in Grant Writing With Lisa Dierker

Lisa DierkerAugust 28, 2019

In the current research landscape, researchers need to develop grant writing skills. In this podcast, Methodology Center Investigator and Professor of Psychology at Wesleyan University Lisa Dierker discusses topics including how to learn what works in grant writing, the best funding mechanisms, and how to approach grant writing as a methodologist or applied researcher. This podcast is intended for graduate students and junior investigators, but there are tips for more senior researchers as well.

Download Podcast 35

Timeline
00:00 – Introductions
00:54 – Lisa’s background in research and grant writing
03:15 – The value of rejected grants
09:26 – Lisa’s favorite funding mechanisms
16:08 – How to get started in grant writing
19:45 – Whom to contact while preparing a grant
25:16 – How applied scientists can incorporate innovative methods into grant writing
28:48 – How methodologists can successfully get their work funded
31:15 – Pursuing grants in a difficult funding environment
34:15 – Top 3 pieces of advice on grant writing

Social Network Analysis With Ashton Verdery

October 10, 2018

In our latest podcast, Ashton Verdery, assistant professor of sociology and demography at Penn State, discusses social network analysis (SNA). One increasingly important use of SNA is to study marginalized populations who are otherwise hard to sample. In health, behavioral, and social sciences, SNA has been used to examine how people relate to one another; how relationships affect the flow of items such as diseases, goods, information, or behaviors; how individual positions in broader network structures affect the risks of contracting diseases, hearing of opportunities, or generating new ideas; and more. In this podcast, Ashton explains the value and challenges of SNA in a behavioral health context. He also discusses projects from his research, including his work studying the heroin crisis in Pennsylvania, kidney transplant candidates, and migrant populations.

Download podcast 34

Timeline
00:00—Introduction
00:31—What is social network analysis (SNA) and why do it?
03:51—Why does SNA interest you?
05:46—Why is SNA valuable in behavioral health?
09:00—Do policy changes affect migrants’ social networks?
13:15—What are the methodological challenges in SNA?
19:17—How are the social network questions different and similar in your research projects on kidney transplants and your research on the heroin crisis?

New Book on Advanced Topics in MOST

Linda M. CollinsAugust 8, 2018

In podcast 33, Methodology Center Director Linda Collins and Faculty Affiliate Kari Kugler discuss the new book from Springer that they edited, Optimization of Behavioral, ​Biobehavioral, and Biomedical Interventions: Advanced Topics. This is the second book on the multiphase optimization strategy (MOST) to be published this year. MOST is an engineering-based framework for optimizing interventions that has been developed by Linda and her collaborators over the past 14 years. In this podcast, Linda and Kari explain the concepts behind and rationale for each of the chapters in the book. Both the book and the podcast explore topics ranging from the development of a conceptual model to the use of concepts from control systems engineering.

Download podcast 33

Timeline
00:00—Introduction
01:08—The differences between the two books on MOST
02:19—Developing a conceptual model for an intervention
04:54—Factorial experiments and types of experimental designs
08:35—Multi-level factorial designs
10:11—Adaptive interventions and MOST
11:38—Control systems engineering in MOST
13:29—Coding data for analysis
16:00—Cost effectiveness analysis in MOST
18:25—Mediation analysis in MOST
20:00—The future of MOST

Audiobook Excerpt: Preface to Linda Collins’ Book on MOST

Linda M. CollinsMay 17, 2018

In this special edition podcast, Methodology Center Director Linda Collins reads the preface to her new book from Springer, Optimization of Behavioral, Biobehavioral, and Biomedical Interventions: The Multiphase Optimization Strategy (MOST). MOST is an engineering-based framework for optimizing interventions, developed by Linda and her collaborators over the past 14 years. In the preface, Linda explains the problem with the current state of intervention research and describes what MOST is and how it can help us address the problem. Then, she explains the content of the book. For researchers who are interested in optimizing interventions, this podcast succinctly introduces the need for and advantages of MOST; the podcast will enable listeners to decide whether to read the entire book.

Download podcast 32

References for the Book and the Articles Discussed in the Podcast

Collins, L. M. (2018). Optimization of behavioral, biobehavioral, and biomedical Interventions: The multiphase optimization strategy (MOST). New York, NY: Springer. Visit Springer’s website

Preface

“In the United States and worldwide, billions of dollars have been spent to develop behavioral, biobehavioral, and biomedical interventions (hereafter referred to simply as interventions) to prevent and treat health problems, promote health and well-being, prevent violence, improve learning, promote academic achievement, and generally improve the human condition. Numerous interventions are in use that are successful in the sense that they have demonstrated a statistically and clinically significant effect in a randomized controlled trial (RCT). However, many are less successful in terms of progress toward solving problems. In fact, after decades of research, as a society we continue to struggle with the very issues these interventions have been designed to ameliorate. Only very slow progress is being made in many areas; in some, the problem continues to worsen. Let us consider two examples in the public health domain, both from the Healthy People goals set every ten years by the United States Centers for Disease Control and Prevention (CDC)…”

New Book on MOST With Linda Collins

February 26, 2018

In this podcast, Methodology Center Director Linda Collins discusses her new book from Springer, Optimization of Behavioral, Biobehavioral, and Biomedical Interventions: The Multiphase Optimization Strategy (MOST)MOST is an engineering-based framework for optimizing interventions that has been developed by Linda and her collaborators over the past 14 years. In the podcast, she describes how MOST can help advance intervention research. She then explains the structure of MOST, using an example from an intervention to help overweight adults lose weight. Finally, she discusses why now is the right time for this book to be published.

Download podcast 31

Podcast Timeline:

00:00—Introduction
00:50—The problem with the status quo in intervention design
03:04—Defining “optimization” and “MOST”
06:57—Describing the phases of MOST
07:39—The preparation phase
11:26—The optimization phase
15:54—The evaluation phase
19:22—How Linda’s thinking about MOST has evolved
21:23—Why is now the right time for this book?

References for the Book and the Articles Discussed in the Podcast

Collins, L. M. (2018). Optimization of behavioral, biobehavioral, and biomedical Interventions: The multiphase optimization strategy (MOST). New York, NY: Springer.

Pellegrini, C. A., Hoffman, S. A., Collins, L. M., & Spring, B. (2014). Optimization of remotely delivered intensive lifestyle treatment for obesity using the multiphase optimization strategy: Opt-IN study protocol. Contemporary Clinical Trials, 38(2), 251-259.

Pellegrini, C. A., Hoffman, S. A., Collins, L. M., & Spring, B. (2015). Corrigendum to “Optimization of remotely delivered intensive lifestyle treatment for obesity using the multiphase optimization strategy: Opt-IN study protocol.” Contemporary Clinical Trials, 45, 468-469.

Collecting Data in Schools with Zena Mello

Zena MelloJanuary 15, 2018

In a relaxed and engaging conversation, Zena Mello, associate professor of psychology at San Francisco State University, discusses the opportunities, complications, obligations, and challenges associated with collecting data in public high schools. She explains the different experiences she had developing relationships and working in two schools that are only minutes apart geographically but sharply divergent in terms of the educational resources available. Her research investigates how adolescents think about time and how that thinking relates to their substance use and other risky behavior.

Download podcast 30

Podcast Timeline:

00:00—Introduction
00:32—Gaining access to high schools for collecting data
12:20—Introducing graduate students to a low-income high school
18:52—Maintaining a relationship with a high school administration
23:30—Gaining access to a high-income high school
30:31—Future directions of Zena’s research

The Past, Present, and Future of Prevention with Mark Greenberg

Mark GreenbergNovember 14, 2017

Mark Greenberg is one of the founders of prevention science as a recognized field. In 1998, he founded The Edna Bennett Pierce Prevention Research Center and served as its director until 2013. In this podcast, he talks with host Aaron Wagner about the founding of the center, its connection to The Methodology Center, the future of prevention science, and more.

Download podcast 29

Download the transcript for podcast 29

Podcast Timeline:

00:00—Introduction
00:37—The genesis of The Edna Bennett Pierce Prevention Research Center and the field of prevention science
06:07—Connections between The Edna Bennett Pierce Prevention Research Center and The Methodology Center
08:15—Mark’s research career
11:22—The impact Edna Bennett Pierce has on the field of prevention research
13:10—The future of prevention research

Getting Started with Secondary Data Analysis

Loren Masters and Kate GuastaferroJune 11, 2017

Secondary data analysis is a high priority for many funding agencies as they try to maximize the information gleaned from funded studies. In this podcast, Methodology Center Research Associate Kate Guastaferro and Methodology Center Data Manager Loren Masters discuss some of the issues and requirements associated with getting access to existing data. This podcast is intended for graduate students or investigators who are new to secondary data analysis. Along with the podcast, users can download an outline of the steps required before conducting a secondary data analysis.

Download podcast 28
Download the transcript for podcast 28
Steps for getting started in secondary data analysis

Podcast Timeline:

00:00—Introductions
02:14—Working with restricted data for qualified researchers
03:53—Working with IRBs
06:50—Data protection plans
11:10—Getting added to existing data use agreements
12:20—Identifying data sets available for secondary analyses
13:22—Working on data from your prior institution
15:47—Potential problems in data procurement
17:26—Closing advice

Ambulatory Assessment with Michael Russell

Michael RussellJanuary 23, 2017

In our latest podcast, Methodology Center Research Associate Michael Russell discusses ambulatory assessment and his pilot project examining self-report data during heavy drinking. In the project, Michael is combining ecological momentary assessment (EMA) of self-reported alcohol use with continuous data from ankle bracelets that measure alcohol intoxication levels through contact with the skin. He is investigating the accuracy of using EMA self-reports as a proxy for such intoxication measures during real-world drinking episodes. He discusses his thoughts on the challenges and opportunities of such data collection, and talks about some of his research using these and other intensive longitudinal data (ILD).

Download podcast 27
Download the transcript for podcast 27

Podcast Timeline:

00:00—Introduction
00:33—Developing an interest in methods
03:07—Ambulatory assessments for understanding substance use
06:29—Examining the accuracy of self-report data on alcohol use
08:30—Practical issues with ambulatory assessment studies
10:09—Methodological issues with ambulatory assessment studies
13:36—Implications for working with IRBs
15:40—Future of ambulatory assessment

Practical Advice on LCA with John Dziak

Aaron Wagner and John DziakDecember 1, 2016

Latent class analysis (LCA) is a widely used tool for identifying subgroups in a population. Many researchers have questions about how to conduct an LCA as responsibly and accurately as possible. In our latest podcast, John Dziak discusses important points to consider when conducting an LCA, like how to tell when an analysis is successful and how to make sure your model is properly identified. John is a Methodology Center research associate who studies LCA, and he is the lead developer of our LCA software, including PROC LCA. Note: this podcast is a companion piece to podcasts 15 and 16 with Stephanie Lanza and Bethany Bray. If you are new to LCA, you may want to start with Podcast 15.

Download podcast 26
Download the transcript for podcast 26

Podcast Timeline:

00:00—Introduction
00:30—What is LCA for?
01:15—Why would someone use LCA?
02:27—How does LCA work?
04:20—How do I select a model?
07:39—How do I know if my LCA worked?
13:45—How do I select items for my model?
18:20—What “percent identified” of random starts is high enough?
19:23—When should I use a higher value in NSTARTS?
20:13—What should I do if my model won’t converge?
23:00—When should I use the RESTRICT option?

Methodological Innovation in HIV Prevention Research with Cara Rice

Cara RiceSeptember 7, 2016

In this short podcast, Methodology Center Postdoctoral Research Associate, Cara Rice, discusses her research examining HIV-risk behavior among sexual minorities. She describes her work collecting survey data among high-risk populations and her application of new methods to these data.  As part of the Methodology Center, Cara has recently used both LCA and TVEM to understand more about the profiles of behavior that increase HIV risk among men who have sex with men (MSM).

Download podcast 25
Download the transcript to podcast 25

Podcast Timeline:

00:00—Introduction
00:30—Becoming an HIV researcher
01:56—Cara’s research
05:45—Applying methods to HIV research
09:34—Collecting extremely personal data
12:03—Applying TVEM to HIV-risk data
14:40—The future of Cara’s research and HIV research

Using MOST to Improve STI Prevention with Kari Kugler and Amanda Tanner

Kari Kugler and Amanda TannerJanuary 27, 2016

In this podcast, we discuss the application of the multiphase optimization strategy (MOST) to the development of an online intervention to reduce sexual risk behavior among college students. Host Aaron Wagner speaks with Kari Kugler, Methodology Center investigator, and Amanda Tanner, assistant professor of public health education at University of North Carolina at Greensboro (UNCG), about the project which is funded by the National Institute on Alcohol Abuse and Alcoholism.

In this study, the researchers will use MOST to strengthen intervention components aimed at reducing risky drinking, risky sex, and their co-occurrence, and then using the strengthened components to form an optimized intervention. The principal investigator of the project is Methodology Center Director Linda Collins. David Wyrick, associate professor of public health education, leads the team at UNCG.

Download podcast 23
Download the transcript for podcast 23

Podcast Timeline:

00:00—Introductions
01:07—What public health problem does the grant address?
03:57—Definition of multiphase optimization strategy
06:45—Other applications of MOST
07:41—Why use MOST on this project?
10:37—How will this project encourage college students to make better decisions?
13:06—Why an online intervention?
14:02—What is incorrect about the term “risky sex?”
15:53—What else should people know about MOST?
16:46—The quality of the project team

Getting Started with TVEM with Stephanie Lanza and Sara Vasilenko

Stephanie Lanza and Sara VasilenkoSeptember 7, 2016

In this short podcast, Methodology Center Postdoctoral Research Associate, Cara Rice, discusses her research examining HIV-risk behavior among sexual minorities. She describes her work collecting survey data among high-risk populations and her application of new methods to these data.  As part of the Methodology Center, Cara has recently used both LCA and TVEM to understand more about the profiles of behavior that increase HIV risk among men who have sex with men (MSM).

Download podcast 22
Download the transcript to podcast 22

Podcast Timeline:

00:00—Introduction
00:30—Becoming an HIV researcher
01:56—Cara’s research
05:45—Applying methods to HIV research
09:34—Collecting extremely personal data
12:03—Applying TVEM to HIV-risk data
14:40—The future of Cara’s research and HIV research

Career Awards, Big Data, mHealth, and Causal Inference with Donna Coffman

Aaron Wagner and Donna CoffmanMay 5, 2015

In this podcast, we talk with Methodology Center Investigator Donna Coffman about the K01 award she received from the National Institutes of Health (NIH) Big Data to Knowledge (BD2K) initiative. Topics include the emergence of big data in NIH-funded research and the practical aspects of applying for a K award. Donna also explains her research on analyzing biosensor data from a parenting study and how her move into big data integrates with her research on causal inference.

Download podcast 21
Download the transcript for podcast 21

Podcast Timeline:

00:00 – Introduction
00:48 – What is a K Award? / Overview of Donna’s K01
03:56 – Training plan in Donna’s K
05:50 – Donna’s background
06:58 – Analyzing biosensor data
09:02 – Causal inference and big data
10:18 – Big data in social, behavioral, and health sciences
11:54 – Applying for a K01
14:05 – Most important attribute of a K01 application

PAMT: Postdoctoral Training in Methods and Prevention with Melissa Boone, Michael Russell, and Sara Vasilenko

Aaron Wagner and Sara Vasilenko

February 26, 2015

In this podcast, we discuss the Prevention and Methodology Training (PAMT) program, which is a collaboration between The Methodology Center and The Bennett Pierce Prevention Research Center. Host Aaron Wagner talks with Melissa Boone, Michael Russell, and Sara Vasilenko, all current or former PAMT postdoctoral fellows. The opportunities and unique features of the program are discussed in under 20 minutes. PAMT also trains Penn State graduate students as predoctoral fellows, but that aspect of the program is not discussed in the podcast.

Download podcast 20
Download the transcript for podcast 20

Podcast Timeline:

00:00 – Introduction
00:54 – What is PAMT? (Melissa Boone)
01:27 – Melissa’s research and her motivation for joining PAMT
03:26 – What’s unique about PAMT (Melissa Boone)
05:06 – Why do a postdoc rather than seek a job? (Melissa Boone)
06:21 – Michael’s research and motivation for joining PAMT
07:31 – Working with prevention and methodology mentors (Michael Russell)
09:07 – Who should apply for PAMT? (Michael Russell)
09:40 – How will PAMT help you in your future? (Michael Russell)
10:19 – Sara’s research and her motivation for joining PAMT
14:00 – Advantage of training in methods and prevention (Sara Vasilenko)
15:30 – How PAMT prepares you for a research career (Sara Vasilenko)

Adaptive Interventions and Personalized Medicine with Susan Murphy

Susan MurphyNovember 4, 2014

In our latest podcast, Amanda Applegate interviews Susan Murphy, Methodology Center principal investigator, Herbert E. Robbins Distinguished University Professor of Statistics, research professor at the Institute for Social Research, and professor of psychiatry at the University of Michigan. The discussion focuses two topics, the sequential, multiple assignment, randomized trial (SMART), which allows scientists to develop adaptive interventions, and the just-in-time, adaptive intervention (JITAI), which uses real-time data to deliver interventions as needed via mobile devices. Susan’s MacArthur Fellowship is also discussed; the podcast was recorded before she was elected to the Institute of Medicine of the National Academies.

Download poscast 19
Download the transcript for podcast 19

Podcast Timeline:

00:00 – Introduction
01:01 – MacArthur Foundation “Genius Grant”
03:31 – Two SMARTs in the field (one to develop an adaptive intervention for alcohol abuse and one to develop an adaptive intervention for helping clinics implement an intervention effectively)
12:44 – The just-in-time, adaptive intervention (JITAI)
18:34 – The future of SMART and JITAI

Physical Activity Research with David Conroy

David ConroyJune 2, 2014

This podcast features David Conroy, professor of kinesiology and human development and family studies at Penn State, and investigator at The Methodology Center. The discussion focuses on David’s research on physical activity and sedentary behavior, how physical activity impacts our lives, and the technological opportunities and methodological challenges of this research. David’s multiple, fascinating projects with other Methodology Center investigators are also discussed.

Download podcast 18
Download the transcript for podcast 18

Podcast Timeline:

00:00 – Introduction
00:45 – Sedentary behavior, active behavior, and your health
06:51 – David’s background
08:25 – Staying healthy in a sedentary society
13:08 – ACT UP interventions to promote activity
19:25 – Promoting health with smartphones
24:31 – Methodological issues: Intensive longitudinal data in this research

Latent Class Analysis (LCA) Part 2: Extensions of LCA with Stephanie Lanza and Bethany Bray

Stephanie Lanza, Aaron Wagner, and Bethany Bray

January 22, 2013

Stephanie Lanza and Bethany Bray discuss extensions of LCA with host Aaron Wagner. Topics include LCA with grouping variables and covariates, latent transition analysis, causal inference in LCA, and LCA with a distal outcome. The discussion assumes that users are familiar with LCA; part 1 provides introductory information.

Download podcast 16
Download the transcript for podcast 16

Podcast Timeline:

00:00 – Introduction
01:00 – Adding grouping variables and covariates to an LCA
12:42 – Causal inference in LCA
17:40 – Predicting distal outcomes using latent class membership
26:26 – Upcoming LCA trainings

References in the podcast:

Lanza, S. T., & Collins, L. M. (2008). A new SAS procedure for latent transition analysis: Transitions in dating and sexual behavior. Developmental Psychology, 42(2), 446-456. PMCID: PMC2846549

Lanza, S. T., Coffman, D. L., & Xu, S. (in press). Causal inference in latent class analysis. Structural Equation Modeling: A Multidisciplinary Journal.

Lanza, S. T., Tan, X., & Bray, B. C. (2013). Latent class analysis with distal outcomes: A flexible model-based approach. Structural Equation Modeling: A Multidisciplinary Journal.

Bray, B. C., Lanza, S. T., & Tan, X. (2012). An introduction to eliminating bias in classify-analyze approaches for latent class analysis (Technical Report No. 12-118). University Park, PA: The Methodology Center, The Pennsylvania State University.

Latent Class Analysis (LCA) Part 1: Common Questions about LCA with Stephanie Lanza and Bethany Bray

Stephanie Lanza and Bethany Bray

November 26, 2012

Methodology Center scientists Stephanie Lanza and Bethany Bray and host Aaron Wagner discuss common, practical issues that arise in latent class analysis (LCA). Issues include selecting indicator variables, selecting a model, determining the necessary sample size, finding LCA software, and getting started in LCA. This is the first in a two-part podcast; the next podcast will address some of our recent research on LCA.

Download podcast 15
Download the transcript for podcast 15

Podcast Timeline:

00:00 – Introduction
01:05 – What is LCA?
02:50 – How is LCA different from factor analysis?
06:48 – Indicator variables
10:54 – Model selection
14:30 – Sample size
19:07 – Software
20:06 – Getting started

References in the podcast

Collins, L. M., & Lanza, S. T. (2010). Latent class and latent transition analysis: With applications in the social, behavioral, and health sciences. New York: Wiley.

Lanza, S. T., Bray, B. C., & Collins, L. M. (2013). An introduction to latent class and latent transition analysis. In J. A. Schinka, W. F. Velicer, & I. B. Weiner (Eds.), Handbook of psychology: Research methods in psychology (2nd Edition, Vol. 2, pp. 691-716). Hoboken, NJ: Wiley.

 

New Methods for Smoking Research with Megan Piper, Lisa Dierker, and Stephanie Lanza

Megan Piper, Lisa Dierker, Stephanie LanzaAugust 28, 2012

Host Aaron Wagner interviews three researchers, Megan Piper of the University of Wisconsin’s Center for Tobacco Research and Intervention, Lisa Dierker of Wesleyan University, and Stephanie Lanza of the Methodology Center. They discuss time-varying effect models, the potential for ecological momentary assessment data to advance smoking research, and an upcoming the special issue of Nicotine and Tobacco Research that will focus on new methods for smoking research.

Download podcast 14
Download the transcript for podcast 14

Podcast Timeline:

00:00 – Introduction
01:30 – Megan Piper: EMA data allows understanding of how quitting smoking works
05:40 – Lisa Dierker: TVEM lets us answer new questions about how people develop smoking behavior
09:12 – Stephanie Lanza: Advancing the methodology of smoking research
13:50 – Stephanie Lanza: Upcoming special issue of Nicotine and Tobacco Research

Reference

Shiyko, M. P., Lanza, S. T., Tan, X., Li, R., &  Shiffman, S. (2012). Using the time-varying effects model (TVEM) to examine dynamic associations between negative affect and self confidence on smoking urges: Differences between successful quitters and relapsers. Prevention Science. PMCID: PMC3372905 doi: 10.1007/s11121-011-0264-z

Using Propensity Scores in Causal Inference with Donna Coffman and Max Crowley

April 13, 2012

Host Aaron Wagner interviews Methodology Center Research Associate Donna Coffman and graduate student Max Crowley. They discuss using propensity scores for causal inference. This is also the topic Donna will present at the upcoming 2012 Summer Institute on Innovative Methods. Propensity scores allow researchers to determine cause and effect in experiments that were not randomized.

Download podcast 13
Download the transcript for podcast 13

Podcast Timeline:

00:00 – Introductions
01:17 – Overview of propensity scores
05:53 – Hypothetical example / including confounders in the model
11:46 – Ways to use propensity scores
17:29 – Resources for using propensity scores

References

Rubin, D. B. (1974). Estimating causal effects of treatments in randomized and nonrandomized studies. Journal of Educational Psychology, 66(5), 688-701. View abstract

Rosenbaum, P. R., & Rubin, D. B. (1984). Reducing bias in observational studies using subclassification on the propensity score. Journal of the American Statistical Association, 79(387), 516-524. View abstract

Rosenbaum, P. R., & Rubin, D. B. (1985). Constructing a control group using multivariate matched sampling methods that incorporate the propensity score. The American Statistician, 39(1), 33-38. View abstract

Adaptive Health Interventions and Causal Inference with Daniel Almirall

Daniel Almirall and Aaron WagnerFebruary 24, 2012

Host Aaron Wagner interviews Daniel Almirall, Faculty Research Fellow at the University of Michigan’s Institute for Social Research and Investigator at The Methodology Center. The discussion focuses on sequential, multiple-assignment, randomized trials (SMARTs), which allow scientists to develop adaptive interventions. Danny works with Susan Murphy, the creator of SMART, to develop and promote this new methodological tool. Danny’s work on causal inference is also discussed.

Download podcast 12
Download the transcript for podcast 12

Podcast Timeline:

00:00 – Introduction and Danny’s background
02:38 – SMART designs for adaptive interventions
08:31 – SMART pilot studies
13:51 – Application of SMART
19:33 – Causal inference
22:39 – Publication update

HealthWise South Africa with Linda Caldwell, Ed Smith, and Linda Collins

Linda CaldwellEdward SmithAugust 5, 2011

Host Michael Cleveland interviews Linda Caldwell, Ed Smith, and Linda Collins. They discuss the history and future of HealthWise, a comprehensive risk-reduction, life-skills curriculum for adolescents in South Africa. The new phase of HealthWise is testing the effectiveness of the intervention’s components. Ed Smith is the associate director of the Prevention Research Center at Penn State; Linda Caldwell is a professor of Recreation, Park and Tourism Management at Penn State; and Linda Collins is the director of The Methodology Center.

Download podcast 9
Download the transcript for podcast 9

Podcast Timeline:

00:00 – Introductions
00:47 – Overview of HealthWise and project site
06:02 – Experimental conditions in the new phase of HealthWise
12:38 – Factorial experimental design
15:40 – Powering a factorial experiment
17:00 – Project time line

Configural Frequency Analysis with Mark Stemmler

Mark StemmlerMay 3, 2011

Host Michael Cleveland interviews Mark Stemmler, professor of psychological methodology and quality assurance and dean of the Faculty of Psychology and Sports Science, Bielefeld University, Germany.  Dr. Stemmler was a visiting scholar at The Methodology Center in fall of 2010. Micheal talks with Mark about configural frequency analysis, a tool for the analysis of multivariate categorical data. They also discuss Dr. Stemmler’s experiences visiting The Methodology Center and teaching at Penn State.

Download podcast 8
Download the transcript for Podcast 8

Podcast Timeline:

00:00 – Introduction
00:48 – Dr. Stemmler’s background and relationship with the Methodology Center
03:52 – Configural frequency analysis (CFA) overview
06:38 – Practical applications of CFA
09:18 – How to learn CFA
11:40 – Dr. Stemmler’s experience visiting Penn State

Where Are They Now? with Bethany Bray

Bethany Bray and Michael ClevelandMarch 10, 2011

Host Michael Cleveland interviews Bethany Bray, Assistant Professor of Psychology at Virginia Tech. Bethany was formerly the Assistant Director and a Research Associate at The Methodology Center. Michael talks with Bethany about her research interests, her experience as a pre-doctoral fellow in the Prevention and Methodology Training (PAMT) program here at Penn State, and her recently released article, “Modeling relations among discrete developmental processes: A general approach to associative latent transition analysis,” in Structural Equation Modeling.

Download podcast 7
Download the transcript for Podcast 7

Missing Data Analysis: Making it Work in the Real World with John Graham

John GarhamOctober 20, 2010

Host Michael Cleveland interviews John Graham, Professor of Biobehavioral Health and Human Development & Family Studies at Penn State, to discuss his recent Annual Review of Psychology article “Missing Data Analysis: Making it Work in the Real World.”  This extended podcast is available as a 2-part download.

Download podcast 5, part 1
Download the transcript for Podcast 5, Part 1

Download podcast 5, part 2
Download the transcript for Podcast 5, Part 2

An Odd Couple in Interdisciplinary Research with Linda Collins and Daniel Rivera

Linda CollinsDaniel RiveraAugust 30, 2010

Host Michael Cleveland interviews an odd couple in interdisciplinary research focused on optimizing behavioral interventions. Social scientist Linda Collins from Penn State and chemical engineer Daniel Rivera from Arizona State talk about their NIH Roadmap Initiative project.

Download podcast 4
Download the transcript for Podcast 4


New Book on Latent Class and Latent Transition Analysis with Linda Collins and Stephanie Lanza

Stephanie LanzaLinda Collins

May 5, 2010

Host Michael Cleveland interviews Linda Collins and Stephanie Lanza, authors of the new book, Latent Class and Latent Transition Analysis: With Applications in the Social, Behavioral, and Health Sciences.

Download podcast 2
Download the transcript for podcast 2

 

The Methodology Center’s New Podcast Series – Methodology Minutes! with Linda Collins

Linda Collins

April 5, 2010

Introduction to The Methodology Center – who are we, what is our mission. Hosted by Michael Cleveland and Linda Collins.

Download podcast 1
Download the transcript for Podcast 1