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  1. Web-Based Research:Issues, Problems and an Example Technique John H. Krantz Hanover College

  2. Outline • Brief History • Issues in Internet Research • An Example Method • Problems and Solutions

  3. History • Email for 2-3 Decades • 1995 • Krantz, Ballard, & Scher (1997) Within Subjects • Reips (1997) Between Subjects • First True Web Experiments • July 1995 List of Online Psychological Research – sponsored by APS for awhile • http://psych.hanover.edu/research/exponnet.html • Almost 200 studies and study sites listed

  4. Why Do Internet Research • Musch & Reips (2000) • Sample Size • Statistical Power • High Speed • Ability to reach participants in other countries • High external or ecological validity • Low cost • Ability to replicate a lab experiment with more power • Special populations

  5. Issues • Is the Sample Representative • Yes and No • Important to remember base of comparison • Ideal vs. Lab • Krantz & Dalal (2000) • Much more diverse that most lab samples • Especially in age and education range • Race is generally limited as is nationality

  6. Sample Characteristics: Gender • Are Internet Samples Male Dominated? • Krantz & Dalal (2000) % Female • GVU 1st (1994) 5% • Reips (1996) English: 43% German: 18% • Krantz, et al. (1997) 44% • Pasveer & Ellard (1998) 3rd Study 71% • More Recent • Caddell & Utt (2004) 77% • Meyerson & Tryon (2003) 45%

  7. Sample Characteristics: Age • Are we still testing college sophomores? • Krantz, et al. (1997) 43% > 30 • Smith & Leigh (1997) 35% > 30 • Pasveer & Ellard (1998) 45% > 25 • GVU 1st 36% > 30 • Caddell & Utt (2004) 60% > 30 • Pattison & Rouse(2003) 16% > 30

  8. Is the College Sophomore be Making a Comeback • Plot of activity of Psychological Research on the Net • Pattison & Rouse (2004) 76% 18-22

  9. Sample Characteristics: Race • How diverse are the samples? • Unfortunately in general samples, diversity is still limited • Krantz et al. (1997) 89% White • Smith & Leigh (1997) 86% White • GVU 10th (1998b) 87% White • O’Neil, Penrod, & Bornstein (2003) 82% White • Meyerson & Tryon (2003) 93% White • However, as will be discussed later, web can make it possible to access special populations

  10. Sample Characteristics: Nationality • Where to do the subjects come from? • Largely North American, even US, even in some European studies • Krantz, et al. (1997) 86% N. Am. • Senior, et al (1999) >80% N. AmThis study was conducted in England.

  11. Is the Data Any Good • Emphatically Yes

  12. Data Quality: Direct Comparisons • A number of studies, still, run both laboratory and internet samples. • Krantz, et al. (1997) • Regression of web means on laboratory samples (even though different types of samples): lab mean = 1*(Web mean) + 0 r2 = .99

  13. Compare to Established Data • Compare web results to previously published data sets • Myerson & Tryon (2003) • Studied Sexual Boredom Scale of Watt & Ewing (1996) • Matched sample characteristics • Found same internal consistency • Form of administration was not a significant factor

  14. Direct Validity Comparison • Use same techniques to validate results • Pasveer & Ellard (1998) • Developed new scale • Internal consistency • Psychomectric properties

  15. Data Validity: Arguments • Reips (2000) • Statistical Power • Limited Sample Population • Limited External Validity • Less than Optimal Voluntariness • Motivational Confounding • Experimenter Bias • Nontransparency • Limitations of what is feasible to research

  16. Interesting Deviations • Stern & Faber (1997) • Milgram’s lost letter technique • Milgram, sent on • Stern & Faber, returned to sender • From doing favor to doing easy task • Often effects are smaller

  17. Getting Subjects: General • http://psych.hanover.edu/research/exponnet.html • Other Pages: • Social Psychology: http://www.socialpsychology.org/expts.htm • The Web Experiment List: http://genpsylab-wexlist.unizh.ch/

  18. Getting Subjects: Special Populations • Advertising • Email Groups • Careful, get permission • Can be thought spam • Netiquette • Discussion Groups • Same, permission

  19. Sample Method for Doing Survey • Birnbaum, M. H. (2001). Introduction to Behavioral Research on the Internet. Upper Saddle River, NJ: Prentice Hall. • Lots of resources at http://ati.fullerton.edu/ • NSF sponsored classes at Fullerton on Social Psychology • One more next January, look for the announcement at this site

  20. First Step: Where to put it • Setting up a server can be easy • Apache web server • http://www.apache.org • Most popular server • Freeware • Any computer connected to web is now a server • May have issues of firewalls & dynamic IP addresses

  21. Second Step: SurveyWiz • In Birnbaum (2001) • Also linked to from http://ati.fullerton.edu/ • Under Birnbaum’s page • Freely available • We will build a very short survey to illustrate

  22. Forms • SurveyWiz uses web forms to collect data • What are forms: • Elements to allow web page viewers to input • This data is then sent back to the server to be processed • SurveyWiz • What the page looks likeMy Take • Can edit it with any web page editor

  23. Examples I have done this year • Caddell & Utt • Pattison & Reese

  24. Third Step: Collecting the data • First way, let Birnbaum do it for you • SurveyWiz is set up this way • <FORM action=http://psych.fullerton.edu/cgi-win/polyform.exe/generic method=post> • FTP://guest:guest99@psych.fullerton.edu • You can type in the address box of your browser. Note that this is FTP site. At the present time, password is guest99, as shown above, and permits download only.

  25. Keeping the Data Local • Second, get this perl script (found at http://psych.fullerton.edu/mbirnbaum/programs/PERL_script2.htm) • The script and instructions are at this site • Written by Billy Schmidt • Also change code in form command • At my school the line reads: • <FORM action=http://psych.hanover.edu/cgi-bin/survey_wiz.pl method=post>

  26. What is CGI • Common Gateway Interface • Method for other programs to interact with web servers • In this case, this perl program takes data from web forms and stores them in a file • Stores data in Excel or SPSS readable files

  27. Fourth Step: Example Data File • Data File • Data coding scheme: all variable names begin two numbers, see example • The perl program sorts the variables by numerical order

  28. Another Method of Survey Generation • Schmit’s Survey Assistant • He manages data • More flexibility • http://or.psychology.dal.ca/~wcs/hidden/home.html

  29. What Do I Need? • At NSF ATI site • List of software resources

  30. What Problems are important • Musch & Reips (2000) – 5 point scale • No control over participant’s behavior 3.6 • No control over motivation 3.4 • Inability of participants to ask questions 3.3 • Nonrepresentative sample 2.9 • Manipulation and fraud 2.4 • Ethical problems 1.5

  31. Problems • Eliminating Multiple Entries • Dropout • Security • Data Integrity

  32. Multiple Entries • People submit too fast, while waiting for feedback • People will fake being two people • Usually have same IP address • SurveyWiz and most other methods, sends the IP address of machine where survey is being taken • Can eliminate more than one from same IP, e.g. Schmidt (1997)

  33. Security & Data Integrity • If on public server, others can access data and download • Others might fake pages to send data (unlikely) • Keep data in non-public directories so only researchers have access • Have CGI check for origin of survey to make sure it is yours (Schmidt, 1997)

  34. Dropout • People will come but not finish • Or data is incomplete • Survey will sends a complete signal to help you track • Can use: (O’Neil, Penrod, & Bornstein, 2003) • Short sweet • Financial incentives. • If multiple pages to survey, several pages warm-up so not drop-out during

  35. Ethical Issues • Should not think of Ethical Issues of Web Research Alone • Compare to Ethics of doing Traditional Research • Not let our comfort with what we have done blind us to those problems

  36. Conclusion • Many Benefits • Easy Methods • Easy Resources • Not alternative to traditional methods • A new tool still needs to be used thoughtfully