SSRC Workshop in Methods (WIM): 2014-2015

Spring 2015

Friday, January 23, 2015

Your Statistical Tool Belt

Stephanie Dickinson

2-4pm, Social Science Research Commons Grand Hall (Woodburn Hall 200)

This workshop will give an overview of how to identify what types of data analysis tools to use for a project, along with basic "DIY" instructions. We will discuss the most common analysis tools for describing your data and performing significance tests (ANOVA, Regression, Correlation, Chi-square, etc.), and how they should be selected based on the type of data and the type of research question you have. We will spend the first hour outlining "what analysis to use when" and the second hour going through an example dataset in SPSS software "Comparing motivations for shopping at Farmer’s markets, CSA’s, or neither." Bring your own data set to work along also.

Stephanie Dickinson is a senior consultant and managing director of the IU Statistical Consulting Center (ISCC).


Friday, January 30, 2015

Getting Started with Qualitative Data Analysis Software

Dr. Kathryn Graber and Dr. Emily Meanwell

2-4pm, Social Science Research Commons Grand Hall (Woodburn Hall 200)

Qualitative data analysis software can be helpful to researchers working with a variety of different types of data, such as video, audio, transcripts, images, and notes that need to be coded and analyzed. The learning curve is steep, however, so starting with it may seem like a daunting task. In this workshop, we will provide a general introduction to working with qualitative data analysis software, focusing on two widely used cross-platform software packages, NVivo and Atlas.ti. Using concrete examples, we will discuss the strengths, weaknesses, and differences of these software packages and provide a general overview of getting started in each. We will also discuss the resources for collecting and working with qualitative data now available through the new Qualitative Data Analysis Lab.

Kate Graber is a new Assistant Professor of Anthropology and Central Eurasian Studies at IU. As a linguistic and sociocultural anthropologist, she conducts multilingual, media-rich fieldwork in Russia and Mongolia. With support from the College, the Department of Anthropology, and the SSRC, she founded the Qual Lab in Fall 2014. It is intended to be a space for faculty and graduate students to try out and gain training on a range of research equipment, including audio and video equipment for field recording, transcription pedals and software, sound and video editing software, and qualitative data analysis software.

Emily Meanwell is the Director of the Social Science Research Commons and the study director for the Sociological Research Practicum. Her research has explored culture, inequality, education policy, and homelessness using a variety of qualitative research methods.

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Friday, February 6, 2015

Systematic Reviewing and Meta-Analysis: How to be a Good Consumer of Scientific Literature Reviews

Dr. Jeffrey Valentine

2-3:30pm, Social Science Research Commons Grand Hall (Woodburn Hall 200)

Policymakers, researchers, and practitioners are increasingly likely to value systematic reviews. However, the quality of systematic reviews varies widely. This workshop will (a) describe the history and logic of systematic reviewing and meta-analysis, (b) demonstrate the ways in which systematic reviews provide a better method for assessing what a body of evidence reveals about the relationships under study, and (c) walk participants through a simple meta-analysis. The workshop will conclude with a core list of questions that can be asked of any systematic review to assess its quality.

Jeff Valentine earned his Ph.D. in Social Psychology from the University of Missouri-Columbia. He is a Professor of Educational Psychology, Measurement, and Evaluation at the University of Louisville. Dr. Valentine is the co-editor, with Harris Cooper and Larry Hedges, of the Handbook of Research Synthesis and Meta-Analysis, 2nd ed., associate editor of Research Synthesis Methods, the co-chair of the training group for the Campbell Collaboration, and a statistical editor in the Cochrane Collaboration. He is also the principal investigator of the What Works Clearinghouse's efforts in postsecondary education (U.S. Department of Education, Institute of Education Sciences), and has authored over three dozen works that use, explain, or seek to improve the methods of systematic reviewing and meta-analysis. 


Friday, February 13, 2015

Introduction to Regression ModeLS for Panel Data Analysis

Dr. Patricia McManus

2-4pm, Social Science Research Commons Grand Hall (Woodburn Hall 200)

Panel methods are appropriate for large-N, small-T data where N represents individual units – for example persons, families, organizations, cities – observed at two or more points in time T. This workshop covers the basic theory underlying the analysis of panel data along with essential terminology, an overview of the kind of data that are appropriate for panel analysis, examples from various disciplines, and a list of common mistakes made when working with panel data models. We then work through an example of an application of the linear error components model from assumptions to estimation, specification tests and interpretation. The workshop concludes with a brief discussion of limitations, extensions, and related approaches.

Dr. McManus is Associate Professor of Sociology at Indiana University, where she studies inequality, poverty and mobility. She teaches graduate courses in applied statistics for the social sciences, including a course on panel data analysis at the University of Michigan’s ICPSR and a spring semester course on longitudinal data analysis. Her work on social mobility processes using longitudinal data techniques has appeared in American Sociological Review, American Journal of Sociology, and Demography.


Friday, February 20, 2015

SURVEY AND ANALYSIS IN 'BABEL'. A PRACTICAL INTRODUCTION TO THE EUROPEAN SOCIAL SURVEY (ESS)

Dr. Bence Ságvári

2-4pm, Social Science Research Commons Grand Hall (Woodburn Hall 200)

The process of globalization and European integration have largely increased interest in cross-national analysis in past decades. In effect, the internationalization of public opinion research has brought unprecedented possibilities for social scientists all over the world. However, doing research in multiple countries where spoken languages, legal systems, and political-cultural traditions differ is a true challenge.

The European Social Survey (ESS) is one of the largest cross national research projects in the social sciences. It was designed to chart and explain the interaction between Europe’s changing institutions and attitudes, beliefs, and the behavioral patterns of its diverse populations. During its six rounds from 2002 to 2012, ESS covered topics of personal and institutional trust, attitudes towards politics and democratic institutions, participation, understanding and evaluation of democratic elements, social exclusion, religion, perceived discrimination, national and ethnic identity, immigration, media and communication, economic morality and welfare attitudes, personal and social well-being, and the perception of life-courses and ageism.

Besides briefly summarizing the development of cross-national surveys in Europe and providing useful information and data sources, this workshop will give an overview of the ESS in general and a detailed  demonstration of the accessibility and usage of its data. This two-hour workshop is designed for anyone who is interested in carrying out cross-national data analysis regarding European countries.

Bence Ságvári is a research fellow at the Hungarian Academy of Sciences Centre for Social Research and at the International Business School (IBS) of Budapest, Hungary. Currently he is a visiting professor at Indiana University. He is the national coordinator for EU Kids Online and for the European Social Survey (ESS) in Hungary. Dr. Ságvári has more than 10 years of research experience in both quantitative and qualitative research. His primary interests are technology, children and young people, and how digital technologies shape people's behavior, values and attitudes. He has a PhD in Sociology from ELTE University in Budapest.

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Friday, February 27, 2015

A Brief Introduction to Multilevel Modeling: Concepts & Applications

Dr. Leslie Rutkowski

2-4pm, Social Science Research Commons Grand Hall (Woodburn Hall 200)

In this two-hour workshop, participants will be provided with a brief overview of multilevel modeling concepts and several applications, including random intercepts and random slopes models. Several examples will be provided along with SAS syntax and a data set will be made available. Participants will have an opportunity to fit several models in SAS and interpret the results.

Leslie Rutkowski is an assistant professor of Inquiry Methodology in the Department of Counseling and Educational Psychology at Indiana University, Bloomington, USA. She earned her PhD in Educational Psychology with a specialization in Statistics and Educational Measurement from the University of Illinois at Urbana-Champaign. Leslie’s research is focused in the area of international large-scale assessment from both methodological and applied perspectives. Her interests include the impact of background questionnaire quality on achievement results, latent variable models for achievement estimation, and examining methods for comparing heterogeneous populations in international surveys.


Friday, March 6, 2015

Introduction to Human Subjects and KC IRB AT IU

Sara Benken

2-4pm, Social Science Research Commons Grand Hall (Woodburn Hall 200)

This workshop will provide an overview of IU's Human Subjects Office and submitting applications through the KC IRB system. We will start with a brief introduction to human subjects, then focus the remaining time on learning how to navigate the IU IRB process.   

Sara Benken is an Associate Director in the IU Human Subjects Office.


Friday, March 27, 2015

Bias in Instrumental Variable Estimates

Dr. Haeil Jung

2-4pm, Social Science Research Commons Grand Hall (Woodburn Hall 200)

The relative size of the treated and untreated groups, or the T/UT ratio, in an analysis sample often diverges from the T/UT ratio in the population (or original sample) because of choice-based sampling, missing values, and data limitations. While divergences of the sample from the population T/UT ratio do not generate bias for many estimators, instrumental variable (IV) estimates are biased by such divergences even when (1) the IV is analytically valid for the population in estimating the Local Average Treatment Effect (LATE) and (2) the treated and untreated group characteristics are intact conditional on the treatment status. We survey published empirical manuscripts to show that this issue is prevalent across various fields. We also prove that the bias in IV estimates, generated by divergences of the sample from population T/UT ratio, is a monotonic function of the difference between the sample and population T/UT ratios. Based on our findings, we suggest possible solutions and how to interpret the biased IV estimates when the true T/UT ratio is unknown.

Haeil Jung is an Assistant Professor in the School of Public and Environmental Affairs

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Friday, April 3, 2015

Statistical Methods in R

Michael Frisby

2-4pm, Social Science Research Commons Grand Hall (Woodburn Hall 200)

R is a flexible and powerful open source statistical programming language, and is one of the fastest growing analytic tools available. Its ever expanding functionality has made it an immensely popular resource to researchers across a wide variety of disciplines.

This two-hour workshop is the second part of a series designed to get you familiar with performing statistical analyses in R. In this workshop, it will be assumed that you have some prior knowledge of R basics. We will focus on implementing some commonly encountered statistical methods in R, including logistic regression, MANOVA, exploratory and confirmatory factor analysis, and hierarchical linear modeling.

Michael Frisby is a statistical consultant at the IU Statistical Consulting Center (ISCC).


Friday, April 10, 2015

Nonparametric statistics for social scientists

Dr. Brad Luen

2-4pm, Social Science Research Commons Grand Hall (Woodburn Hall 200)

Parametric statistical methods may perform poorly when their assumptions are violated. For example, the t-test may have low power when samples are not from normal distributions, while linear regression will predict poorly when the relationships between variables is not linear. "Nonparametric statistics” refers to a broad range of techniques that avoid restrictive parametric assumptions about populations or data. We will explore two very different nonparametric methods: Rank tests, where hypotheses are tested by comparing the ranks of samples, and smoothing splines, which fit smooth curves and surfaces to data that may not be linear. We will implement these techniques in R, and discuss when it may or may not be appropriate to use these techniques instead of their parametric counterparts.

Brad Luen received his Ph.D in statistics from the University of California, Berkeley, where he studied the assessment of probabilistic forecasts for earthquakes. He is a lecturer in the Department of Statistics.


Friday, April 17, 2015

Abductive Analysis and the Search for Mechanisms: Semiotic Chains as a Bottoming-out Processual Level in Qualitative Research

Dr. Iddo Tavory

2-4pm, Social Science Research Commons Grand Hall (Woodburn Hall 200)

In Abductive Analysis Stefan Timmermans and myself argue that sociologists need to cut through inductivism and deductivism, and posit the generative surprises of research at the center of qualitative theorizing. We then argue that the strongest evidence in most qualitative research—and the best way to locate “surprises“ in the research process—arises through tracing chains of meaning-making in action and interaction. This presentation will expound on this second point, comparing this pragmatist processual account to other notions of mechanism-base explanation in the social sciences, and especially in “analytical sociology.” As we argue, semiotic chains provide a uniquely adequate bottoming-out level since it traces the building blocks of action and interaction without making untenable assumptions about human nature and rationality.

Iddo Tavory is an Assistant Professor of Sociology at NYU. Iddo’s overarching interest is in the interactional patterns through which people come to construct and understand their lives. His book Abductive Analysis: Theorizing Qualitative Research (co-authored with Stefan Timmermans) outlines a pragmatist approach to the relation among theories, method, and observations in qualitative research (University of Chicago Press, 2014). His second book, Summoned, is an ethnography of an Orthodox Jewish neighborhood in Los Angeles, as well as an essay on the co-construction of identification, interaction and the patterning of social worlds (forthcoming, 2015, University of Chicago). His publications have appeared, among other places, in the AJSASRSociological Theory and Theory and Society

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Friday, April 24, 2015

The Grammar of Graphics: An Introduction to ggplot2

Jefferson Davis

2-4pm, Social Science Research Commons Grand Hall (Woodburn Hall 200)

In The Grammar of Graphics, Leland Wilkinson laid out a systematic way to think about statistical graphics and the presentation of quantitative data. The package ggplot2 by Hadley Wickham implements of Wilkinson's system for the language R.

The talk will cover the following:

- What are statistical graphs and what are some ways to talk about them?
- Examples of common plot types done in ggplot2.
- Using ggplot2 to display common statistical transformations.
- Grouping and faceting data in ggplot2.
- Using themes to add polish to graphs.

The talk requires no familiarity with ggplot2 or other libraries. Some familiarity with base R, however, will be useful.

Jefferson Davis is a software consultant with Research Analytics. He has worked on several projects that have used R and R libraries. Sample projects include visualizing economic simulations, simplifying demographic data, and running semantic analyses on large text files.