1. Copyright © 2016 Wolters Kluwer All Rights Reserved Chapter 7 Experimental Design I— Independent Variables

2. The Research Process Evidence-based practice Search for answers Design and development of a study Funding Human and animal use approval Pilot studies Preliminary data Design and development of a study Funding Human and animal use approval Pilot studies Preliminary data Conduct of the study Collection of the data Laboratory analysis of data Statistical analysis of data Manuscript preparation Peer review Publication of manuscript The Body of Knowledge Anecdotal observations Scientific literature base The Body of Knowledge Anecdotal observations Scientific literature base 2 Copyright © 2016 Wolters Kluwer All Rights Reserved If found If not found If rejected If accepted

3. Key Terms Alternate/research hypothesis Between-group/-subject independent variable Bias Blind Confounding or intervening variable Constant Control group Counterbalancing Dependent variable Double blind Exclusion criteria Experimental research External validity Hawthorne effect Inclusion criteria Independent variable Internal validity Multivariate Non-experimental research Null hypothesis Placebo effect Power Quasi-experimental research Research design Treatment/intervention Univariate Variable Within-group/-subject independent variable 3 Copyright © 2016 Wolters Kluwer All Rights Reserved

4. Planning the Research Design Research design is the process by which investigators determine how to answer their research question(s) Flaws in research design typically cannot be overcome by editing or statistical analysis 4 Copyright © 2016 Wolters Kluwer All Rights Reserved

5. Identifying Variables A variable is some characteristic or factor that can have different values and is either subject to change or can be manipulated as an intervention Variables may be independent, dependent, constant, or confounding 5 Copyright © 2016 Wolters Kluwer All Rights Reserved

6. Identifying Variables Independent Variable Intentionally controlled or manipulated Treatment or interventionMay be multiple levelsMay be group classificationKnown factor Dependent Variable Outcome for which researcher hopes to elicit an effect “What is measured”Unknown factor 6 Copyright © 2016 Wolters Kluwer All Rights Reserved

7. Independent Variables: Levels 7 Copyright © 2016 Wolters Kluwer All Rights Reserved Examining the effects of different doses of a drug or supplement is an example of multiple levels of a single independent variable How different doses affect male and female mice is an example of multiple independent variables Fig. 7-1

8. Independent Variables: Types 8 Copyright © 2016 Wolters Kluwer All Rights Reserved Between-group (or between-subjects) independent variable: different group of subjects for each level of the variable Within-group (or within- subject) independent variable: each subject is tested at each level of the independent variable Fig. 7-1

9. Identifying Variables Between-Group/-Subject Well suited to animal studies Random group assignment can reduce within-group variability; matching might be preferred Within-Group/-Subject Each subject serves as his/her own control More demanding of the participants Powerful statistical design Reduces sample size and need for randomization Requires longer time period, including accounting for wash-out 9 Copyright © 2016 Wolters Kluwer All Rights Reserved

10. Overview of Research Design Dimensions DesignPrimary UseRandomized?Degree of Control Retrospective or Prospective? Emphasis on Validity Non- Experimental Description, examine relationships NoLowEither Quasi- Experimental Causal inferences NoLow/mod erate EitherExternal True Experimental Causal inferences YesHighProspectiveInternal 10 Copyright © 2016 Wolters Kluwer All Rights Reserved Table 7-4

11. Experimental Design: Control Group Control group: measured at the same time points as the treatment group(s) but receives no treatment Placebo: dummy treatment that does not affect the dependent variable(s) Blinding: keeping participants (single blind) and ideally both participants and study personnel (double blind) naïve to the study treatment to limit bias 11 Copyright © 2016 Wolters Kluwer All Rights Reserved

12. Experimental Design: Control Group Placebo effect: subjects receiving the placebo may experience a benefit even though they aren’t receiving any treatment Hawthorne effect: subjects may perform better due to being observed 12 Copyright © 2016 Wolters Kluwer All Rights Reserved

13. Experimental Design: Selecting Subjects Identify the study population, and obtain a representative sample Weigh the ability to improve retention (convenience sample) against having a more representative sample The degree to which the sample represents the population of interest affects the power of the study Inclusion criteria are the stated subject characteristics Exclusion criteria restrict subject participation 13 Copyright © 2016 Wolters Kluwer All Rights Reserved

14. Experimental Design: Controlling Variability & Bias Using randomization or matching to assign subjects to groups reduces other factors affecting the dependent variable Controlling for confounding or intervening variables reduces threats to internal validity Minimizing signal-to-noise ratio better enables the impact of the independent variable on the dependent variable to be observed Systematic errors occur when measurement error is in one direction Random errors may occur in any direction and typically have a net zero effect 14 Copyright © 2016 Wolters Kluwer All Rights Reserved

15. Summary Research design requires balance, weighing the pros and cons of a number of experimental choices There is a trade-off between controlling variables and real- world applicability Planning is key for avoiding confounding factors 15 Copyright © 2016 Wolters Kluwer All Rights Reserved