Up A Brief Quiz Experimental Effects Identification


Chapter 10:

Design of Experimental Research
in Communication




I. The Notion of an Experiment

experiment: the study of the effects of variables manipulated by the researcher in a situation in which all other variables are controlled, completed for the purpose of establishing causal relationships
confounding: when variation from one source is mixed (or confused) with variation from another source so that it is impossible to know whether effects are due to the impact of either variable separately or some combination of them

 --deception: an ethical problem created when research participants have been either (1) uninformed that an   experiment was being conducted or (2)   intentionally misled about the nature of the study in which they are participating

   A.  Questions and Hypotheses in Experimental Designs
         --hypotheses in experiments are phrased to explore cause-
           and-effect relationships


--experiments require that variables be capable of manipulation

experimental independent variables:  independent variables that are manipulated by the researcher

   B. The Concept of Control

control: methods researchers use to remove or hold constant the effects of nuisance variables
elimination and removal: removing a nuisance variable from the experimental setting
holding constant: limiting the range of intervening variables so that they are equal across studies (by 1. limiting the population, 2. using subjects as their own controls, 3. counterbalancing [rotating the sequence in which experimental treatments are introduced to subjects in an effort to control for extraneous variables, such as fatigue or cumulative learning effects])
matching: pairing subjects on some variable on which they share equal levels and then assigning them to experimental or control conditions
blocking: adding a nuisance variable into the design as another independent variable of interest
randomization: assigning participants so that each event is equally likely to belong to any experimental or control condition
--respondents may be selected at random from the population; they also

   may be assigned at random to experimental or control conditions
statistical control: use of statistical tools such as analysis of covariance and partial correlation to hold a nuisance variable constant
 --additional sources of error:

halo effect: influences from strong positive or negative impressions of a source of communication that affect other ratings that follow
placebo effect: an occurrence in which subjects show change even though there is no experimental treatment
John Henry effect: subjects' inconsistency with their normal activity because they try extra hard when participating in experiments
"do nothing" control groups: since experimental and control groups should share all things except the experimental variable, control groups that "do nothing" are apt to differ from the treatment groups in additional ways

II.  Experimental Validity and Invalidity

experimental invalidity: errors that prevent researchers from drawing unequivocal conclusions

    A. Internal Invalidity
         --if all sources of internal invalidity
are not controlled, it is not
           possible to claim that any observed effects were caused by
           the independent variable in the experiment

internal invalidity: the presence of contamination that prevents the experimenter from concluding that a study's experimental variable is responsible for the observed effects

·  history: events not controlled by the researcher that occur during the
experiment between any pretest and posttest;

·  selection: sampling biases in selecting or assigning subjects to experimental or control conditions;

·  maturation: changes that naturally occur over time;

·  testing: alterations that occur when subjects are tested and made testwise or anxious in ways that affect them when they are given a second test;

·  instrumentation: changes in the use of measuring instruments from the pretest to the posttest, including changes in raters or interviewers who collect the data in different conditions;

·  statistical regression: shifts produced when subjects are selected because of very high or very low scores on some test and then changes on that measurement are tracked in the experiment;

·  experimental mortality: biases introduced when subjects differentially (nonrandomly) drop out of the experiment;

·  interaction of elements: effects created by the interaction of selection biases with differential levels of maturation, history, or any other source of variation.

    B. External Invalidity

external invalidity: the degree to which experimental results may not be generalized to other similar circumstances

·  interaction of testing and the experimental variable: (pretest sensitization) a defect created when the pretesting makes subjects either more or less sensitive to the experimental variable

·  interaction of selection and the experimental variable: effects created by sampling groups in such a way that they are not representative of the population since they are more or less sensitive to the experimental variable than other subsamples from the same population

·  reactive arrangements: elements in the experimental setting that make subjects react differentially to the experimental arrangements rather than to the experimental variable alone

·  multiple treatment interference: if subjects are exposed to repeated additional experimental treatments, they may react in ways that are not generalizable to subjects who are uncontaminated by such additional independent variables

III. Specific Experimental Designs

A.  Notation for Experimental Designs


O:  an observation of the study's dependent variable
X: the experimental variable
R: randomization

B.  Pre-Experimental Designs


          1. one shot case study

one shot case study: an experimental treatment is introduced and researchers look at effects on some output (dependent) variable without benefit for a control group

          2. one group pretest-posttest study

one group pretest-posttest: a case study with an additional pretest so that subjects can serve as their own controls

          3. static group comparisons

static group comparisons: a design adding a control group, but the two groups are not known to be comparable

    C. True Experimental Designs


        1. Pretest-Posttest Control Group
            --researchers avoid using "change scores" since (1)
              change scores may not have distributions that make them
              easy to interpret with standard statistical tools, (2) change
              scores have lower reliability  than the original measures

pretest-posttest control group design: a design including pretesting and posttesting individuals in a randomly assigned experimental group and control group

        2.  Solomon Four Group Design

Solomon four group design: a design that adds control groups to examine pretesting effects directly

        3.  Posttest Only Control Group

posttest only control group design: a design that controls for pretest sensitization by deleting the pretest entirely

    D. Factorial Designs

factorial designs: experimental designs that include more than one independent variable

         1.   Uses in Research

factors: variables that are broken down into levels; a.k.a. "variable factors"
levels: categories of each factor

--single subject experiments: experiments in which experimental
  conditions are presented to or deleted from the same subjects over

--limitations: (1) most applicable to questions of individual difference, rather than patterns across people; (2) limited   generalizability prevents examining hypotheses of social significance to most communication researchers; (3) limits the sorts of statistical tools that might be used to help analyze results.

         2. Interpreting Factorial Results


             a. Main effects

main effects: dependent variable effects from independent variables separately

             b. Interaction effects

                 --interactions are indicated by lines that are not
                   parallel to each other when relationships are graphed
                --unlike ordinal interactions, when crossed interactions are
                   found, researchers are forbidden from interpreting the
                   main effects for the variables involved since such
                   interpretations would be misleading
IV.  Some Elements Found in Good Experiments

interaction effects: dependent variable  effects from independent variables taken together
ordinal interaction: if lines drawn in graphic displays of the effect are not parallel and do not cross each other, the pattern is called an ordinal interaction
disordinal interaction: patterns of graphic displays of the effect that occur when lines drawn for each independent variable cross each other (a.k.a. "crossed interaction")

      A.  Securing Informed Consent and Debriefing

            In addition to the information that must be communicated in
            any informed consent undertaking (see Chapter 9),
            experimenters are expected to inform participants of:
the experimental nature of the treatment; 2. the services
            that will or will not be available to the control group(s) if
            appropriate; 3. the means by which assignment to
            treatment and control groups will be made; 4. available
            treatment alternatives if an individual does not wish to
            participate in the research or wishes to withdraw once a
            study has begun; and 5. compensation for or monetary 
            costs of participating including, if appropriate, whether
            reimbursement from the participant or a third-party payer
            will be sought.

--Using an introductory script.

--Using a debriefing script.


      A. The Pilot Test

pilot studies (also called “pilot tests”): studies usually involving small samples of people (sometimes as small as ten or twenty people) who take part in an experiment to determine any difficulties with experimental materials

      B. Manipulation Checks

manipulation check: a researcher's measurement of a secondary variable to determine that an experimental variable actually operated in a study
quasi experiments: experimental work where random assignment and control are not possible
--time series designs: measurement of participants across different
--separate sample posttest designs: posttests completed from another
  group of participants that are close but not assured to be equivalent to
   the experimental group
--counterbalanced designs: designs that introduce several different
   experimental treatments presented to participants in different orders or

      C. Care in Interpretation
           1. Resisting the Tendency to Infer Long Term Effects from
               Short Term Experiments
           2. Searching for Nonlinear Relationships
           3. Desirability of Multiple Dependent Variables