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QUANTITATIVE RESEARCH METHODS. Irina Shklovski. Quantitative Research Methods. Include a wide variety of laboratory and non-laboratory procedures Involve measurement…. Quantitative Research Methods. Measurement Populations and Sampling Random Assignment Generalizability.

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quantitative research methods2
Quantitative Research Methods
  • Include a wide variety of laboratory and non-laboratory procedures
  • Involve measurement…
quantitative research methods5
Quantitative Research Methods
  • Measurement
    • Populations and Sampling
    • Random Assignment
    • Generalizability
quantitative research methods6
Quantitative Research Methods
  • Measurement
    • Populations and Sampling
    • Random Assignment
    • Generalizability
  • Time
    • Cross-sectional studies & single experiments
    • Longitudinal studies & repeated measures
quantitative research methods7
Quantitative Research Methods
  • Method
    • Experiments & Quasi-experiments
    • Behavioral Measures
    • Questionnaires & Surveys
    • Social Network Analysis
    • Archival and Meta-Analysis
what we will talk about today
What we will talk about today
  • Measurement
    • Population & Sampling
    • Random Assignment
    • Generalizability
  • Method
    • Experiments & Quasi-experiments
    • Questionnaires & Surveys
measurement sampling
Measurement – Sampling
  • Specify your population of concern
  • Sampling
    • Selecting respondents from population of concern
    • Random sampling
    • Systematic selection
    • Stratified sampling
    • Convenience sampling
    • Snowball sampling
sampling biases
Sampling Biases
  • Non-response bias
    • Be persistent
    • Offer incentives and rewards
    • Make it look important
  • Volunteer bias
    • Some people volunteer reliably more than others for a variety of tasks
random assignment
Random assignment
  • Different from random sampling
  • Mostly used for experiments or quazi-experiments
  • Protects against unsuspected sources of bias
  • Does NOT guarantee to balance out the differences between participants
  • Chance is LUMPY
generalizability
Generalizability
  • How do you know that what you found in your research study is, in fact, a general trend?
  • Does A really, always cause B?
  • If A happens, is B really as likely to happen as you claim? Always? Under certain conditions?
association vs causality
Association vs. Causality

Thanks toSara Kiesler for these graphs!

experiments quasi experiments
Experiments & Quasi-experiments
  • ex·per·i·ment
    • Pronunciation: \ik-ˈsper-ə-mənt also -ˈspir-\
    • Function: noun
    • Etymology: Middle English, from Anglo-French esperiment, from Latin experimentum, from experiri
    • Date: 14th century
  • An operation or procedure carried out under controlled conditions to discover an unknown effect or law, to test or establish a hypothesis, or to illustrate a known law
experiments quasi experiments15
Experiments & Quasi-experiments
  • Key feature common to all experiments:
    • To deliberately vary something in order to discover what happens to something else later
    • To seek the effects of presumed causes
an experiment is
An Experiment is
  • A controlled empirical test of a hypothesis.
  • Hypotheses include:
    • A causes B
    • A is bigger, faster, better than B
    • A changes more than B when we do X
  • Two requirements:
    • Independent variable that can be manipulated
    • Dependent variable that can be measured
experiments in research
Experiments in Research
  • Comparing one design or process to another
  • Deciding on the importance of a particular feature in a user interface
  • Evaluating a technology or a social intervention in a controlled environment
  • Finding out what really causes an effect
  • Finding out if an effect really exists
remember
Remember
  • Experiments explore the effects of things that can be MANIPULATED
  • (but there is a caveat)
types of experiments
Types of Experiments
  • Randomized – units/participants assigned to receive treatment or alternative condition randomly
  • Quazi – no random assignment
  • Natural – contrasting a naturally occurring event (i.e. disaster) with a comparison condition
if your study involves experiments
If your study involves experiments
  • Experimental design:Shadish W.R., Cook T.D. & Campbell P.T. (2002) Experimental and Quasi-Experimental Design for Generalized Causal Inference. Boston, Mass: Houghton Mifflin
  • Experimental data analysis:Bruning, J. L. & Kintz, B. L. (1997). Computational handbook of statistics (4th ed.). New York: Longman.
questionnaires surveys
Questionnaires & Surveys
  • Self-report measures
    • Questionnaires & surveys
    • Interviews
    • Diaries
  • Types
    • Structured
    • Open-ended
questionnaires surveys22
Questionnaires & Surveys
  • Advantages
    • Sample large populations (cheap on materials & effort)
    • Efficiently ask a lot of questions
  • Disadvantages
    • Self-report is fallible
    • Response biases are unavoidable
response biases
Response biases
  • Relying on people’s memory of events & behaviors
    • Emotional states can “prime” memory
    • Recency effects
    • Routines are deceiving
  • Social desirability
    • Solution: none that are simple
  • Yea-saying
    • Solution: vary the direction of response alternatives
general survey biases
General Survey Biases
  • Sampling – are respondents representative of population of interest? How were they selected?
  • Coverage – do all persons in the population have an equal change of getting selected?
  • Measurement – question wording & ordering can obstruct interpretation
  • Non-response – people who respond differ from those that do not
design is key
Design is KEY
  • Format – booklet, printed vertical, one-sided
  • Question ordering – earlier questions can prime answers to later questions
  • Page layout – group similar items & use consistent fonts and response categories
  • Pre-testing – conduct think-alouds with volunteers demographically similar to expected participants
common problems
Common Problems
  • Avoid complicated & double-barrel questions
    • Complexity increases errors & non-response
  • Navigation is paramount – make sure the survey is EASY to follow
  • Open-ended questions
    • The size of the field allotted will determine the number of words
  • Incentive is key
    • BUT amount differences have little impact
if your study involves surveys
If your study involves surveys
  • Designing surveys:Dillman, D. A., Smyth, J. D., & Christian, L. M. (2009). Internet, mail, and mixed-mode surveys : the tailored design method (3rd ed.). Hoboken, N.J.: Wiley & Sons.Fowler, F. J. (1995). Improving survey questions : design and evaluation. Thousand Oaks: Sage Publications.
  • Analyzing data:Cohen, J., Cohen, P., West, S., & Aiken, L. (2003). Applied multiple regression/correlation analysis for the behavioral sciences (3rd ed.). Mahwah, NJ: Lawrence Erlbaum Associates.
so what
So… what?
  • Difference between quantitative methods is in the questions they can answer
  • There are a LOT of methods and even more statistical techniques
  • Regardless of the method, if it’s not an experiment, you CAN NOT prove causation
things we did not talk about
Things we did NOT talk about
  • Reliability assessments
  • Validity assessments
  • Statistical analysis of data
  • Interpretation of results