Chapter 4: Fundamental Research Issues

Validity

Truth or accuracy.

Construct validity

Concerns whether our methods of studying variables are accurate. Refers to the adequacy of the operational definition of variables: Does the operational definition of a variable actually reflect the true theoretical meaning of the variable?

Internal validity

The accuracy of conclusions about cause and effect.

External validity

Whether findings of the study can be generalised to other settings.

Variable

Any event, situation, behaviour, or individual characteristic that varies. For some variables, the values will have true numeric, or quantitative properties.

Operational definition

The set of procedures used to measure or manipulate a variable. Some variables must be defined in terms of the specific method used to measure or manipulate it. Two important benefits: 1) the task of developing an operational definition of a variable forces scientists to discuss abstract concepts in concrete terms; 2) operational definitions also help researchers to communicate their ideas with others.

Relationships between variables

When both variables have values along a numeric scale, many different "shapes" can describe their relationship.

Positive linear relationship

Increases in the values of one variable are accompanied by increases in the values of the second variable.

Negative linear relationship

Increases in the values of one variable are accompanied by decreases in the values of the other variable.

Curvilinear relationship

Increases in the values of one variable are accompanied by systematic increases and decreases in the values of the other variable. Direction of the relationship changes at least once.

No relationship

The graph is simply a flat line.

Correlation coefficient

Numerical index of the strength of relationship between variables.

Uncertainty

Implication that there is randomness in events; scientists refer to this as random variability in events that occur.

Nonexperimental methods

Relationships are studied by making observations or measures of the variables of interest.

Variables are observed as they occur naturally.

Nonexperimental

Both variables are measured.

nonexperimental

Correlational method.

nonexperimental

Problems: 1) it can be difficult to determine the direction of cause and effect; 2) researchers can face the third-variable problem.

nonexperimental

Experimental method

Involves direct manipulation and control of variables. The researcher manipulates the first variable of interest and then observes the response.

It attempts to eliminate the influence of all potential confounding third variables on the dependent variable.

Third-variable problem

Extraneous variables may be causing an observed relationship.

Direction of cause and effect

Knowledge of the correct direction of cause and effect in turn has implications for applications for research findings.

Confounding variable

A variable that is not controlled in a research investigation. In an experiment, the experimental groups differ on both the independent variable and confounding variable.

Experimental control

All extraneous variables are kept constant. Accomplished by treating participants in all groups in the experiment identically; the only difference between the groups is the manipulated variable.

Sometimes it is not feasible because experimentation would be unethical or impractical.

Randomisation

Participants are assigned to groups randomly.

The number of potential confounding variables is infinite, and sometimes it is difficult to keep a variable constant, of which randomisation eliminates the influence of such variables. Extraneous variables are just as likely to affect one experimental group as it is to affect the other group.

Independent variable

The cause. Variable that is manipulated.

Dependent variable

The effect. The variable that is observed.

Field experiment

Independent variable is manipulated in a natural setting.

Artificiality of experiments

The high degree of control in the laboratory setting may sometimes create an artificial atmosphere that may limit either the questions that can be addressed or the generality of results.

Participant variables

(Also called subject variables or personal attributes)

Are characteristics of individuals, such as age, gender, ethnic group, nationality, birth order, personality, marital status, etc. These are by definition non experimental and must be measured.

Description of behaviour

The goal of much research is to describe behaviour; in those cases, causal inferences are not relevant to the primary goals of the research.

Successful predictions of behaviour

When researchers develop measures to predict future behaviour, they must conduct research to demonstrate that the measure does, in fact, relate to the behaviour in question.

Advantages of multiple measures

No method is perfect, and no single study is definitive.