Quantitative Research Design Backdrop to Multivariate Analysis

Quantitative Research Process Research Objectives Background of the Problem Research Questions Hypotheses Method Data Analysis Discussions and Implications Limitations

Research Proposal A written statement of the research design Including the purpose of the study, definition of the problem, research methodology and details of the procedures

Sampling Sampling terminology  Sample  Population  Population element  Census Why sample?  Pragmatic reasons  Accurate and reliable results

Probability versus Nonprobability Sampling Probability sampling  Simple random sampling  Systematic sampling  Stratified sampling  Proportional versus disproportional strata  Cluster sampling  Multistage area sampling Nonprobability sampling  Convenience sampling  Judgment sampling (purposive sampling)  Quota sampling  Snowball sampling

Sample Size Confidence level

Variables Categorical (classificatory) variable Continuous variable Dummy variable Independent variable Dependent variable

Tips for Questionnaire Design Two basic criteria  Relevance  Accuracy Opened-ended v.s. fixed-alternative questions Types of fixed-alternative questions (mutually exclusive)  Dichotomous-alternative question  Determinant-choice question  Frequency-determination question  Checklist question

The Art of Asking Questions Avoid complexity: use simple language Avoid leading and loaded questions  Counterbiasing statement  Split-ballot technique Avoid ambiguity: be as specific as possible Avoid double-barreled items Avoid making assumptions Avoid burdensome questions that may tax the respondent’s memory

Some Issues about Questionnaire Design Order Bias  Funnel technique  Anchoring effect  Filter question  Pivot question Best Layout  Multiple-grid question Pre-testing and Revising

Survey Research Advantages of survey research:  Quick  Inexpensive  Efficient  Accurate

Survey Research Total Error Random sampling error Systematic error Respondent error Administrator error Nonresponse error Response bias Deliberate falsification Unconscious misrepresentation Acquiescence bias Extremity bias Interviewer bias Auspices bias Social desirability bias Data processing error Sample selection error Interviewer error Interviewer cheating

Experimental Research A research investigation in which conditions are controlled so that an independent variable(s) can be manipulated to test a hypothesis about a dependent variable. Allows evaluation of causal relationships among variables while all other variables are eliminated or controlled.

Basic Issues in Experimental Design Manipulation of the independent variable Experimental treatments Experimental and control groups Experimental treatment levels More than one independent variable Selection and measurement of the dependent variable Demand characteristics Debriefing (ethical issue)

Experimental Validity External validity (generalizability) Internal validity  The ability of an experiment to answer the question of whether an experimental treatment was the sole cause of changes in a dependent variable or whether the experimental manipulation did what it was supposed to do.  History  Maturation  Testing  Instrumentation  Selection  Mortality

Measurement– types of scales Nominal scale  Frequency in each category  Percentage in each category Ordinal scale (rank order)  Median  Range  Percentile ranking Interval scale (rank order in equal intervals)  Mean  Standard deviation  Variance Ratio scale (arithmetic operations on actual quantities)  Geometric mean  Coefficient of variation

Reliability Old Rifle New Rifle New Rifle Sunglare (low reliability) (high reliability) (reliable but not valid)

Reliability Analysis Cronbach’s alpha cofficeint (Cronbach, 1951) Refer to the applicability of obtained scored as an estimate of “true” scores if all possible tests or all possible scores were available What is acceptable reliability?  0.85 or higher  Depends on the numbers of item and the situation