Research Approaches

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Research Approaches• Internal Validity• External Validity

“A study that is fetchingly realistic might bring us no closer to the truth than one that seems painfully contrived” (Myers & Hansen, 2006, p. 63).

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Dimensions of Research

• Antecedent Manipulation–Treatments–Independent variable (IV)

• Imposition of Units–Behavioral measures–Dependent variable (DV)

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Dimensions of Research

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True Experiments

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Nonexperimental Approaches

• Phenomenology – attending to and describing one’s own experience

• Case studies – outside observer records an individual’s experiences & behaviors

• Field studies – research method conducted in the field using a variety of techniques

– Field experiments – a type of field study?

• Archival studies – reexamine existing data for a new reason

• Qualitative studies – data are verbal descriptions rather than numbers

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• Phenomenology -Description of one’s own immediate experience

Examples: pain in my neck (C5 vertebrae) the Purkinje effect

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• Case studies -Descriptive records of another individual’s experiences or behavior.Evaluative case studies – case compared to hypothetical “normal” psychological diagnosis – DSM-IV? Now DSM-5http://www.psychiatry.org/psychiatrists/practice/dsm/dsm-5/online-assessment-measures

Deviant case analysis – deviant case compared to “normal” for significant differences.e.g. Mednick, 1969 – ANS of schizophrenic children functions different compared to normal controls.

http://www.psychiatry.org/psychiatrists/practice/dsm/dsm-5/online-assessment-measures



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• Field studies -Studies done in situ, in real-life settings as opposed to the laboratory.

Compare to - A field Experiment in Chicago (p. 86).

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• Naturalistic observation - a technique of observing behaviors as they occur spontaneously in the natural setting.

e.g. dominance hierarchies in social groups.

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• Systematic observation - a technique of using specific rules in a pre-arranged way to objectively record observations.

Female sexual receptivity (rodents only)Lordosis- 1. darting, 2. ear wiggling 3.

inverted back and 4. tail diversion

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• Participant-observer studies - the researcher becomes part of the group being studied.

Undercover roid guy… just what baseball needed!

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• Archival study - already existing records are reexamined for a new purpose. E.g. data on crime, death rates, education levels, salaries housing patterns and disease rates are accessible to researchers.

BioinformaticsGene database

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• Qualitative research relies on words rather than numbers

Is there a paradigm shift occurring?

Self-reports personal narratives expression of ideas, memories, feelings and thoughts

Contemporary or Empirical Phenomenology1. Researcher self-reflects on experiences

related to the phenomenon2. Others provide verbal or written descriptions

of experiences 3. Accounts of the phenomenon are gathered

from literature, art, television, the internet and other sources

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Phenomenology is used as part of qualitative research

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Correlational and Quasi-Experimental Designs

Chapter 5

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Correlational Designs

Determine the degree of relationship between two traits, behaviors or events; predict one set from another.

• Antecedents are preexisting• Degree of imposition of units - high• Tend to be higher in external validity

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Correlational Designs

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Quasi-experimental Designs

Can seem like an experiment, but subjects are not randomly assigned to treatment conditions.

• Antecedent control varies• Degree of imposition of units - high• Tend to be higher in external validity

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Quasiexperimental Designs

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Example of a Quasiexperiment

Lighting condition – fluorescent vs incandescent.

Subjects – from company A (fluorescent lights) or B (incandescent).

Performance measure – productivity.Can cause-effect be established with

confidence?

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Pearson Product-Moment Correlation Coefficient (r )

Most common procedure for calculating simple correlations – relationship between pairs of scores for each subject. Three outcomes are possible:

• Positive relationship• Negative relationship• No relationship

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ScatterplotsVisual representations of the scores belonging to

each subject in a study. Each dot = two scores (x,y) from one subject.

• One score places the dot along the horizontal axis (x) and the other score places it along the vertical (y) axis.

• Regression lines (of best fit) represent the mathematical equation that best represents the relationship between the two measured scores.

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Hypothetical RelationshipsA. B.

C.

Negative r = -.72 Positive r = +.69

No correlation r = -.02

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Variable X Variable X

Variable X

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Four possible causal directions of a correlation

• Given a strong positive relationship between childhood aggressiveness and watching violent TV (r = +.70).

1) Watching violent TV aggressiveness2) Aggressiveness watching violent TV3) Aggressiveness watching violent TV4) Both are caused by a third variable

(unknown or not measured, e.g., parental supervision)

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Coefficient of determination

• Estimates the amount of variability in scores on one variable that can be explained by the other variable.

• E.g., if r = .56, then r 2 = .31. • 31% of the variability in scores on variable X

can be accounted for by variable Y.• An r 2 ≥ .25 can be considered a strong

association.

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Regression equation

Positive r = +.56

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Variable X: calculate mean and SY intercept

slopeY

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Regression Equation

• Given the score on one variable you can predict the score on the other if you know:

– The value of r– Average scores of X and Y (the means)– Standard deviation (S) of X and Y

Y = Y + r [Sy / Sx] (X – X)

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Multiple Regression

• Used to predict the score on one behavior from the scores on others included in the analysis.

• The regression equation provides beta weights for each predictor (indicating their importance)

• Beta weights can simply be reported or used in an advanced correlational analysis to construct causal sequences for the behaviors.

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Multiple Correlation

• Intercorrelations among 3 or more behaviors (R)

• Can not explain why the 3 measures are related but it may suggest that a “third variable” is important.

• Influence of one variable is held constant while measuring the correlation between the other two – partial correlation

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Causal Modeling

• Advanced correlational techniques• provide information about the direction of

the cause and effect sequences among variables. Two techniques:

1. Path analysis2. Cross-lagged panel designs

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Path Analysis

• Creates models of possible causal sequences when several related behaviors are measured

• Beta weights from multiple regression analysis are used to evaluate the direction of cause and effect from correlated variables.

• Internal validity is low (correlational data), consequently causal statements can not be made.

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Path Analysis

Monitoring IntrusiveThoughts

PsychologicalDistress

PerceivedRisk

.20* .25**

.30** .37**

Internal validity?Third variables?* p < .05, ** p < .01

From Schwartz, Lerman, Miller, Daly, and Masny (1995)

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Cross-Lagged Panel Design

• Uses relationships measured over time to suggest causal models.

• The same pair of related behaviors or characteristics are measured at two separate time points for each subject.

• Can only suggest the direction of causal relationships (not conclusive).

• Bidirectional causation and the third variable problem cannot be ruled out.

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Cross-Lagged Panel Design

Hypothetical Cross-Lagged Panel design

Size of Vocabulary

Time watchingTV

r = .20

Age 3

Time watchingTV

Size of Vocabulary

Age 8

r = .14

r = .41

r = .05r = .07 r = -.59

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• Subjects cannot be randomly assigned to different treatments

• Quasi-treatments are formed based on a particular event, characteristic or behavior of interest.

• E.g., gender differences in sleep patterns.• Low internal validity.

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• Subjects may be exposed to different treatments, but without random assignment (e.g. the lighting-productivity study)

• There is a lack of control over other potential confounds (i.e., an inability to hold all else constant except for the treatment condition).

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Ex Post Facto Studies

• Ex Post Facto – systematic examination of the effects of subject variables (characteristics) without manipulation.

• Low Antecedent Manipulation• High Imposition of Units• Greater external validity

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Nonequivalent Groups

• A manipulation is carried out but subjects are not randomly assigned to groups

• E.g. the lighting experiment yet again• Internal validity can be increased by

controlling extraneous variables after careful consideration of potential confounds.

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Longitudinal Designs

• Measure the behavior of the same group of subjects across time.

• A form of within-subject design• Important for studying growth and

development and aging• Retaining subjects may be difficult

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Cross-sectional Studies

• Investigates changes across time by comparing groups of subjects already at different stages at a single point in time.

• Typically requires more subjects than the longitudinal study.

• Subjects may differ in ways other than those being studied (similar to Ex post facto).

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Pretest/Posttest Design

• Investigates the effects of a treatment by comparing behavior before and after the treatment.

• Practice effects (pretest sensitization)• Outside influences cannot be ruled out• Low internal validitye.g., exposure to cocoa on cognitive

performance

Research Approaches

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