EKOS Research Associates Inc. Interactive Voice Response: The Past, the Present, and Into the Future Presentation to: The MRIA Ottawa Chapter January 21,

Slides:



Advertisements
Similar presentations
CHAPTER 9, survey research
Advertisements

Online Privacy Survey Results Conducted: December 2011.
2010 Research on Respondents tVox Data May, 2010 © Harris Interactive.
1 Sampling Telephone Numbers and Adults, and Interview Length, and Weighting in the California Health Survey Cell Phone Pilot Study J. Michael Brick, Westat.
Chapter 11: Collecting Data by Communication. Key Issues for Collecting Information by Communication.
Brown, Suter, and Churchill Basic Marketing Research (8 th Edition) © 2014 CENGAGE Learning Basic Marketing Research Customer Insights and Managerial Action.
Copyright 2010, The World Bank Group. All Rights Reserved. Estimation and Weighting Part II.
Overview: Online Surveys Vasja Vehovar University of Ljubljana, Slovenia Handbook of Online Research Methods Colloquium March 2007.
Sample Design (Click icon for audio) Dr. Michael R. Hyman, NMSU.
© 2002 Prentice-Hall, Inc.Chap 1-1 Statistics for Managers using Microsoft Excel 3 rd Edition Chapter 1 Introduction and Data Collection.
Documentation and survey quality. Introduction.
The Excel NORMDIST Function Computes the cumulative probability to the value X Business Statistics: A First Course, 5e © 2009 Prentice-Hall, Inc
Examining Best Practices for Sampling and Weighting Dual Frame Surveys Liz Kantor Advised by Dr. David Redlawsk Rutgers, The State University of New Jersey.
McGraw-Hill/Irwin Business Research Methods, 10eCopyright © 2008 by The McGraw-Hill Companies, Inc. All Rights Reserved. Chapter 9 Surveys.
Basic Business Statistics (8th Edition)
Error and Sample Sizes PHC 6716 June 1, 2011 Chris McCarty.
FINAL REPORT: OUTLINE & OVERVIEW OF SURVEY ERRORS
Cell phone problem and alternative approaches Chris McCarty University of Florida PHC 6716 May,
Sampling Design & Sampling Procedures Chapter 12.
Surveying Cell Phone-Only Canadians: Looking at the Possibilities Presentation to the Marketing Research and Intelligence Association Ottawa Chapter February.
Joint Canada/U.S. Health Survey Catherine Simile, National Center for Health Statistics Patrice Mathieu, Statistics Canada Ed Rama, Statistics Canada NCHS.
Sample Design.
Chapter 10 Surveys McGraw-Hill/Irwin Copyright © 2011 by The McGraw-Hill Companies, Inc. All Rights Reserved.
CHAPTER FIVE (Part II) Sampling and Survey Research.
Introduction to Survey Research. What kind of data can I collect? Factual Knowledge Factual Knowledge Cognitive Beliefs or Perceptions Cognitive Beliefs.
McGraw-Hill/Irwin Business Research Methods, 10eCopyright © 2008 by The McGraw-Hill Companies, Inc. All Rights Reserved. Chapter 9 Surveys.
Statistics 3502/6304 Prof. Eric A. Suess Chapter 2.
Chapter 5 Section 3 Part 1.  Often when we hear of a sample we do not know the truth behind the sampling process.  The whole truth about opinion polls.
Nonresponse issues in ICT surveys Vasja Vehovar, Univerza v Ljubljani, FDV Bled, June 5, 2006.
Learning Objectives Problem Definition and the Research Process Copyright © 2004 John Wiley & Sons, Inc. CHAPTER Two.
CHAPTER 12 – SAMPLING DESIGNS AND SAMPLING PROCEDURES Zikmund & Babin Essentials of Marketing Research – 5 th Edition © 2013 Cengage Learning. All Rights.
Chapter Nine Copyright © 2006 McGraw-Hill/Irwin Sampling: Theory, Designs and Issues in Marketing Research.
Descriptive and Causal Research Designs Copyright © 2010 by the McGraw-Hill Companies, Inc. All rights reserved. McGraw-Hill/Irwin.
Chapter Five Copyright © 2006 John Wiley & Sons, Inc. Copyright © 2004 John Wiley & Sons, Inc. Copyright © 2004 John Wiley & Sons, Inc. Survey Research:
A Latent Class Call-back Model for Survey Nonresponse Paul P. Biemer RTI International and UNC-CH Michael W. Link Centers for Disease Control and Prevention.
Data Collection Method
Internet Surveys & Future Works In Official Statistics 1 The 4th International Workshop on Internet Survey Methods, Sept. Statistical Center, Statistics.
Sampling Class 7. Goals of Sampling Representation of a population Representation of a population Representation of a specific phenomenon or behavior.
McGraw-Hill/Irwin Business Research Methods, 10eCopyright © 2008 by The McGraw-Hill Companies, Inc. All Rights Reserved. Chapter 9 Surveys.
Brown, Suter, and Churchill Basic Marketing Research (8 th Edition) © 2014 CENGAGE Learning Basic Marketing Research Customer Insights and Managerial Action.
C1, L2, S1 Political Polls in New Zealand Dru Rose.
Planning an Applied Research Project Chapter 8 – Sampling Issues in Research © 2014 John Wiley & Sons, Inc. All rights reserved.
© 2010 Pearson Prentice Hall. All rights reserved Chapter Data Collection 1.
Chapter 8 Improving Decisions with Marketing Information.
Statistics for Managers Using Microsoft Excel, 4e © 2004 Prentice-Hall, Inc. Chap 1-1 Statistics for Managers Using Microsoft ® Excel 4 th Edition Chapter.
Growing Challenges to State Telephone Surveys of Health Insurance Coverage: Minnesota as a Case Study Supported by a grant from the Minnesota Department.
Copyright 2010, The World Bank Group. All Rights Reserved. Reducing Non-Response Section A 1.
Surveying Cell Phone Numbers in the United States Synthesis and Future Research Needs Paul J. Lavrakas, Ph.D. DC-AAPOR Workshop September 4, 2008.
Survey Research Chapter 7. The Nature of Surveys  Definition  Advantages  Disadvantages –Errors.
McGraw-Hill/Irwin Copyright 2006 The McGraw-Hill Companies, Inc. All rights reserved Chapter 11 Surveys and Interviews.
6: Descriptive and Causal Research Designs. 6-2 Copyright © 2008 by the McGraw-Hill Companies, Inc. All rights reserved. Hair/Wolfinbarger/Ortinau/Bush,
Survey Research. In Case of a System Glitch… After forming into your usual teams: –Create a brief survey that seeks to discern citizens’ attitudes about.
SECTION 4.1. INFERENCE The purpose of a sample is to give us information about a larger population. The process of drawing conclusions about a population.
Survey Research.
Data Collection: Enhancing Response Rates & Limiting Errors Chapter 10.
McGraw-Hill/IrwinCopyright © 2014 by The McGraw-Hill Companies, Inc. All rights reserved. SURVEYS Chapter 10.
Survey Research. Sampling and Inference June 9, 2008 Ivan Katchanovski, Ph.D. POL 242Y-Y.
Effects of Sampling and Screening Strategies in an RDD Survey Anthony M. Roman, Elizabeth Eggleston, Charles F. Turner, Susan M. Rogers, Rebecca Crow,
The Use of Random Digit Dialing in Household Surveys: Challenges and Changes Chris Chapman 2008 IES Research Conference Washington, DC June 11, 2008
McGraw-Hill/IrwinCopyright © 2014 by The McGraw-Hill Companies, Inc. All rights reserved. SAMPLING Chapter 14.
1 of 29Visit UMT online at Prentice Hall 2003 Chapter 1, STAT125Basic Business Statistics STATISTICS FOR MANAGERS University of Management.
Descriptive Research & Questionnaire Design. Descriptive Research Survey versus Observation  Survey Primary data collection method based on communication.
Investigating the Potential of Using Non-Probability Samples Debbie Cooper, ONS.
Presented by: Khaleel S. Hussaini PhD Bureau Chief, Public Health Statistics Division of Public Health Preparedness Judy Bass Arizona’s BRFSS Coordinator.
E-Reading Rises as Device Ownership Jumps BY: KATHERINE ZICKUHR AND LEE RAINIE.
Surveys Jan 21. Samples and populations Need for sampling Goal: representative sample Methods of sampling – Quota Sampling – Volunteer samples – Probability.
Use of Interactive Voice Response technology in collecting community data: Lessons from LiveWell Colorado Tristan Sanders BA, Diane K King PhD, Bonnie.
Membership in Online Research Panels presentation of results from a BRI Omnibus telephone survey April 29, 2010 asdf.
Surveys of Consumers: Mixed Mode Experiments
How media cover election polls in the U.S.
Presentation transcript:

EKOS Research Associates Inc. Interactive Voice Response: The Past, the Present, and Into the Future Presentation to: The MRIA Ottawa Chapter January 21,

EKOS Research Associates Inc. Current State of Survey Research Massive changes in polling and survey research Biggest is drift from live CATI to online methods  Fast, cheap  Self-administered  Multi-media capabilities BUT non-probability online methods lack representativeness  Non-coverage issues  Not randomly selected Another option: Interactive Voice Response (IVR) for both data collection and probability panel construction

EKOS Research Associates Inc. IVR Advantages and Disadvantages (1) Advantages:  Perhaps closest to national population  Avoids social desirability  Cost-effective  Higher reliability due to large sample sizes Disadvantages:  Higher non-response  Survey must be shorter  Some design limits  Reputation  Intrusiveness

EKOS Research Associates Inc. IVR Advantages and Disadvantages (2) Rob Ford election as recent illustration of IVR success  Coverage issue (older, vulnerable)  Social desirability issues (closet supporters) 2008 federal election (best of RDD polls) U.S. mid-terms (mixed results – clear lessons) IVR is good for short polls and for population seeding a panel BUT live follow-up is crucial:  Verification  Explanation  Create dossier of key demographics

EKOS Research Associates Inc. Demographic Analysis – IVR vs. CATI Population % IVR Land-line % CATI- Land-line % IVR Dual Frame Land-Mobile % Age Group < Education HS College University Immigration Born in Canada Not

EKOS Research Associates Inc. Response Rate – IVR vs. CATI IVR – Landline Sample Live Interviewer CATI – Landline Sample Final Disposition Unused 00 A Invalid numbers 14,3954,829 B Unresolved 5,7078,083 C Non-responding, unknown eligibility 00 D Ineligible2,200 (estimated)1,129 E Non-responding, eligible 37,92212,009 F Completed interviews 1,9763,009 TOTALS 60,00029,059 Response Rate Empirical Method (f+d)/(b+d+e+f+c) 4.33% (unadjusted) 8.7% (adjusted) 17.08%

EKOS Research Associates Inc. Conclusions (1) IVR in and of itself is not a polling method  Still need rigorous sampling, callbacks, etc.  But provides excellent equilibrium of cost and quality in appropriate circumstances Hugely neglected area (largely reputational), but will improve IVR is vastly superior to non-probability online polls or even live CATI omnibus (purpose built IVR versus uncertain context of omnibus) Response rate issue overstated; non-response about half live CATI

EKOS Research Associates Inc. Conclusions (2) In the United States, when pollsters had the accuracy of their results tested during the 2008 primary and election year, the two companies employing IVR were rated first and eighth among more than forty companies by the leading website monitoring polling in the U.S. AAPOR has indicated that “the use of either computerized telephone interviewing (CATI) techniques or interactive voice response (IVR) techniques made no difference to the accuracy of estimates” in U.S. pre-primary polls The Pew Research Center has reported that “the mean error among IVR polls [in the 2008 U.S. election] was slightly lower than among those with live interviewers”.

EKOS Research Associates Inc. Emerging Issues Education and civic literacy/interest bias Better sampling and weighting No long form census? The cell phone only household Broader credibility of scientific samples/ evidence based research

EKOS Research Associates Inc. For more information: Frank Graves, President t: