Psych220 Quiz2

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Research Methods Second Edition

CHAPTER 4

Michael W. Passer

RESEARCH METHODS | CONCEPTS AND CONNECTIONS Michael W. Passer | Second Edition

DEFINING AND MEASURING VARIABLES

CHAPTER 4

RESEARCH METHODS | CONCEPTS AND CONNECTIONS Michael W. Passer | Second Edition

Types of Variables (part 1)

QUALITATIVE AND QUANTITATIVE VARIABLES

A variable is any factor or attribute that can assume two or more values.

Qualitative variables represent properties that differ in kind; value levels are categories.

Quantitative variables represent properties that differ in amount; value levels exist on continuum from high to low.

Types of Variables (part 2)

DISCRETE AND CONTINUOUS VARIABLES

Discrete variables are found between any two adjacent values; no intermediate values are possible.

Continuous variables are found between any two adjacent scale values; intermediate values are possible.

Example of a Line Graph and a Bar Graph

What kinds of variables do you see?

Figure 4.2 Example of a line graph and a bar graph. (a) A line graph. The variable plotted along the x-axis, sound intensity, is a quantitative variable that is continuous in principle, even though in operational form it is discrete. (b) A bar graph. The variable plotted along the x-axis, type of music, is a qualitative variable.

Types of Variables (part 3)

INDEPENDENT AND DEPENDENT VARIABLES

An independent variable is the presumed cause in a cause–effect relation.

In experiments, it is a factor that researchers manipulate or systematically vary in order to assess its influence on some behavior or outcome.

A dependent variable is the presumed effect in a cause–effect relation in an experiment.

It is the behavior or outcome that the researcher measures to determine whether the independent variable has produced an effect.

Try This!

Identify the presumed cause and effect represented in each question.

Then determine and create labels for the independent and dependent variables.

Compared to traditional navigation technologies, will modern technologies reduce the number of navigation errors that cockpit crews make during taxiing maneuvers?

Is the speed with which people react to stimuli affected by the intensity of those stimuli?

See page 113 in the text for additional questions to consider.

Did You Figure It Out?

Figure 4.3 Independent and dependent variables at a conceptual level. Based on the phrasing of the bulleted questions on page 113.

The factors that are conceptually viewed as the independent variable and dependent variables are shown in this figure. You may have chosen different labels for the variables, which is fine, as long as your label captures the gist of the factor and is properly placed as the presumed cause or the effect.

Remember

Manipulating independent variables is the hallmark of experimentation.

The same variable can be an independent variable or dependent variable, depending on the research question.

A study may examine how an independent variable influences two or more dependent variables.

A study may examine how multiple independent variables simultaneously influence one or more dependent variables.

Types of Variables (part 4)

HYPOTHETICAL CONSTRUCTS

Many concepts that behavioral scientists study represent psychological states or processes that are hypothesized to exist but cannot be directly observed.

The characteristics or processes are inferred from measurable behaviors or outcomes.

This occurs via operationalization.

Types of Variables (part 5)

MEDIATOR AND MODERATOR VARIABLES

Mediator variable

Provides a causal link in the sequence between an independent variable and a dependent variable

Helps explain why an independent variable influences a dependent variable

Types of Variables (part 6)

MEDIATOR AND MODERATOR VARIABLES

Moderator variable

Is a factor that alters the strength or direction of the relation between an independent and dependent variable

Informs us about when and for whom an independent variable produces a particular effect

Types of Variables (part 7)

MEDIATOR AND MODERATOR VARIABLES

(a) A direct link is proposed between an independent variable and dependent variable. (b) A mediator variable is added, providing an explanatory causal link between the independent and dependent variable.

Defining Variables

CONCEPTUAL DEFINITIONS

Involves explicitly defining a specific concept, so it can be systematically measured

OPERATIONAL DEFINITIONS

Refers to defining a variable in terms of the procedures used to measure or manipulate it

OPERATIONAL DEFINITIONS IN EVERYDAY LIFE

Refers to definitions used in many parts of daily life

Can You Identify the Planning Errors and the Decision Errors?

Figure 4.8 Pilot navigation errors on the airport surface. The percentage of simulated flights on which crews made a planning or decision error, as a function of the cockpit technology that was available. (a) Planning errors. (b) Decision errors. (Copyright 2006. From Pilot navigation errors on the airport surface: Identifying contributing factors and mitigating solutions. The International Journal of Aviation Psychology by Hooey, B. L. et al. Reproduced by permission of Taylor & Francis LLC [http://www.tandfonline.com].)

Scales of Measurement (part 1)

Measurement is the process of systematically assigning values (numbers, labels, or other symbols) to represent attributes of organisms, objects, or events.

The term systematic means that values are assigned according to some rule.

Scales of measurement refers to rules for assigning scale values to measurements.

Scales of Measurement (part 2)

In order of least precise to most precise:

NOMINAL

ORDINAL

INTERVAL

RATIO

Can You Provide an Example of Each Scale?

See Figure 4.10 for examples.

Measurement Accuracy, Reliability, and Validity (part 1)

ACCURACY OF MEASUREMENT

Accuracy of a measure represents the degree to which the measure yields results that agree with a known standard.

Systematic error (also called bias) is a consistent degree of error that occurs with each measurement.

Measurement Accuracy, Reliability, and Validity (part 2)

RELIABILITY OF MEASUREMENT

Reliability of a measure is assessed by examining its consistency.

Random measurement error is the random fluctuations that occur during measurement and cause the obtained scores to deviate from a true score.

The greater the random error, the less reliable a measuring instrument will be.

What does reliability have to do with random measurement error?

Measurement Accuracy, Reliability, and Validity (part 3)

RELIABILITY OF MEASUREMENT

Random error can be introduced by:

Participants’ characteristics

Measurement setting or procedures

Measuring instrument

Other factors

Measurement Accuracy, Reliability, and Validity (part 4)

RELIABILITY OF MEASUREMENT

Test–retest reliability

Split-half reliability

Internal reliability or internal-consistency reliability

Cronbach’s alpha

Interobserver (Interrater) Reliability

Measurement Reliability

Researchers can estimate the reliability of a measure in several ways. This figure highlights three approaches.

Measurement Accuracy, Reliability, and Validity (part 5)

VALIDITY OF MEASUREMENT

Just because a measure is reliable, this does not necessarily mean it is valid.

Validity refers to whether a measure actually assesses the attribute that it is claimed to assess.

Measurement Accuracy, Reliability, and Validity (part 6)

VALIDITY OF MEASUREMENT

Face validity concerns the degree to which the items on a measure appear to be reasonable.

Content validity represents the degree to which the items on a measure adequately sample the entire set of items that could have been included.

Criterion validity focuses on how well a measure can predict or estimate a criterion.

Predictive validity and concurrent validity represent two types of criterion validity.

Measurement Accuracy, Reliability, and Validity (part 7)

VALIDITY OF MEASUREMENT

Construct validity is demonstrated when a measure has consistently been shown to assess the underlying construct that it is claimed to assess.

Convergent validity and discriminant validity, along with content and criterion validity, provide evidence for the construct validity of a measure.

Measurement Validity

Figure 4.12 Measurement validity. Researchers want to draw valid inferences based on the measures they use. They gather several types of evidence to establish measurement validity.

Are Our Measures Any Good?

Scholars may differ in terms of how they approach validity and reliability, but they converge on two key points:

Reliability is a necessary but insufficient condition for validity.

Construct validity is the most fundamental validity.