COMM 250 Agenda - Week 10

Housekeeping

• C2 – Returned to You Today

• RP1 – Due Today (IM Surveys)

• TP3a – Due Tomorrow

Lecture

• RAT4

• Review RP1

• Experiments

Review: The Research Process

Conceptualization• Start with / Develop a Theory and Hypotheses

Planning & Designing Research• Selecting Variables of Interest (IV, DV, Control vars)• Operationalize all Variables (i.e., How to measure the vars?)• Design a Study to Test Hypotheses

Methods for Conducting Research• Plan the Study and Collect the Data

Analyzing & Interpreting Data• Run Statistics and Interpret Results

Re-Conceptualization• Back to the Drawing Board

Experimental ResearchPurpose• To Control Variables (in order)

• To Attribute the Effects to the IV; that is,

• To Infer Causality

Types of Experiments• Pre-Exp. - Typically no Comparison Group

• Quasi-Exp. - IV is manipulated OR Observed, NO Random Assignment of Subjects

• Full Experiments - IV is “manipulated,” Random Assignment of Subjects

Experimental Research (continued)

Experimenters Create Situations . . .• to Control Variables (in order to . . .)• to Attribute Observable Effects to the IV; that is . . .• to Infer Causality

Control by ‘Exposing’ Subjects to an IV• Manipulating (exposure to) an IV (the “Active Var.”)• Observing (exposure to) an IV (the “Attribute Var.”)

Control by “Ruling Out" Initial Differences• Random Assignment• Pretests

Correlation & Causality (Review)

Correlation• Two variables are related (as one varies, the

other varies predictably)

Causation3 “Necessary & Sufficient” Conditions:

• Two variables must be shown to be related

• The IV must precede the DV in Time

• The relationship cannot be due to another “extraneous” variable

Experimental DesignsPre-Experiments (“Pseudo-Experiments”)

1-Group, Posttest Only• Produces a Single Score• E.g.: Exam in School

1-Group, Pretest-Posttest• Produces a Difference Score• E.g.: Evaluation of Corporate Training

Non-Equivalent Groups, Posttest Only• Also Called “Static Group Comparison”• No Random Assignment to Groups• E.g.: Comparing Test Scores for a Training Class to a

Group Who Did Not Take the Training

Experimental DesignsQuasi-Experiments (“Field Experiments”)

1-Group, Time Series Design• Series of Pretests (Baseline) Treatment Series of Posttests

• E.g.: Monitoring the Effects of Blood Pressure Medicine

• Problems: Sensitization, Sleeper Effect, No Comparison Group

Quasi-Equivalent Groups, Pretest-Posttest• Non-Random Assignment to (Treatment, Control) Groups

• Produces a Difference Score

• E.g.: Study of College Classes• Problems: Equivalence (History, etc.)

Quasi-Equivalent Groups, (Multiple) Time Series Design• Combines the Two Designs Above

• Problems: Sensitization, Equivalence, Sleeper Effect

Experimental DesignsFull ExperimentsEquivalent Groups, Pretest-Posttest • Equivalence = Random Assignment of Subjects to Groups• Experiments Provide Control; Reveal Causality (in the Lab) • E.g.: Testing a New Chemotherapy Drug

Equivalent Groups, Posttest Only• Relies on the Random Assignment• Initial Differences COULD Cause Any Observed Effect

• E.g.: Lab Study of New Messaging System

Solomon Four-Group• Combines the Two Designs Above

• Checks for Pretest (Sensitization) Effects• Checks Whether Random Assignment “Worked”

Experimental DesignsFactorial Designs • Multiple IVs (“Factors”); Typically One DV

• Can Be Pre-, Quasi-, or Full Experiments

• Most Common: Quasi- and Full

• Most Common: Posttest Only

Examples –H1: The more competent at comm, the higher income one earns.

2x2 Factorial Design• IVs: Comm Competence (Lo, Hi); Gender (F, M)• DV: Income

3x2x2 Factorial Design• IVs: Competence (L, M, H); Gender (F, M); Occup (BC, WC)

• DV: Income

(Possible) 2 x 2 Factorial Design

Independent Variables (IVs)• Comm Competence (Hi / Lo)

• Gender (M / F)

Dependent Variable (DV)• Likability Score (could have others)

Control Variable• (Positive/Negative) Attitude

2 x 2 Factorial Design - Example

• IVs: Comm Competence, Gender • DV: Income• Subjects: 20 per cell• Control for: Age, Education, Location

Female Male

Low Comm Competence

20 20

High Comm Competence

20 20

Experimental Research (Review)

Experimenters Create Situations . . .• to Control Variables (in order to . . .)• to Attribute Observable Effects to the IV; that is . . .• to Infer Causality

Control by Exposing Subjects to an IV• Manipulating (exposure to) an IV (the “Active Var.”)• Observing (exposure to) an IV (the “Attribute Var.”)

Control by “Ruling Out" Initial Differences• Random Assignment• Pretests

Hypotheses (Review)

Two-Tailed Hypotheses• Non-directional – researcher predicts a

relationship, but does not specify the nature

• “Comm Competence is related to Annual Income.”

One-Tailed Hypotheses• Directional – researcher predicts both a

relationship AND the direction of it

• “The more Competent one’s Comm, the higher one’s Annual Income.”

In-Class Team Exercise # 8 - Part I

First Do as Individuals, then produce a Team Version:

1) Design a Factorial Experiment to answer these questions:Which can be read faster on a web site - plain text (plain black letters on a white

background, no links) or text supplemented in some way?

What other variables might affect a user’s ability to read text? (Name 3 and then Choose one for Step 2)

2) Draw a table of the design - at least 3 levels of one variable, 2 of another (you choose the second IV)• Label the 2 IVs and Label Their Levels

3) Write out 2 Hypotheses (H1, H2):• One Predicting Effects of IV 1, the other the Effects of IV 2

4) Declare the DV (It is in your H1, H2)

5) List Two (“People”) Variable you Should “Control for”

Review: Variables of Interest

Independent – influences another variable• IV = “Predictor” variable

Dependent – variable influenced by another• DV = “Outcome” variable

Control – variable one tries to control for• Could “keep constant,” balance across groups,

or extract in the statistical analysis

• Control Var = “Concomitant” variable

Extraneous Variables

Intervening Var – explains relation bet IV, DV

• “The a Person’s Comm Competence (CC) (the IV), the the Salary (the DV).”

• Since Competence, per se, doesn’t get you $, “Job Function” is an Intervening Var.

Extraneous Variables (continued)

Confounding Var – obscure effects• “Surpressor” Var. reduces the effect of an IV• CC could # of Friends, but also difficulty of

chosen job, which in turn time for friends.

• “Reinforcer” Var. increases the effect of an IV• CC could # of Friends, but also # of events one

attends, which in turn would further # of friends.

Lurking Var – explains both IV and DV• Perhaps the var “Extroversion” affects both CC

and # of Friends.

In-Class Team Exercise # 8 - Part IIProduce a Team Version only:How does talking on a cell phone affect driving?

Design a 3 x 2 Factorial Experiment (draw a Table)You Must Use These IVs:• Level of Driving Experience (Pick 3 Levels)

• Type of Distraction (Pick 3: Cell Phone, Changing CDs, You choose #3)

Write out 2 Hypotheses (H1, H2):• Your DV should be: MPH deviation from the average speed

on the road

• One Predicting the Effects of Driving Experience• One Predicting Differences Due to Type of Distraction

Label the 2 IVs and Label Their LevelsList Two Other Variables you Should “Control for”