VARIABLESVARIABLES

VARIABLESVARIABLES

• Definition: Variables are properties or characteristics of people or communication phenomena that take on different values demographic characteristics

personality traits

communication styles or competencies

constructs

• in order to be a variable, a variable must vary (e.g., not be a constant), that is, it must take on different values, levels, intensities, or states

Variables Must Vary!

• “Female” is not a variable; if everyone in a study is female, then “female” is a constant.– female versus male is a variable– degree of femininity is a variable– females’ sexual orientation is a variable

DEFINITIONSDEFINITIONS

• Variable: “any entity that can take on a variety of different values” (Wrench et al, 2008, p. 104)– gender

– self-esteem

– managerial style

– stuttering severity

• attributes, values, and levels are the variations in a variable (p. 106)– Attribute: political party:

– Value: Democrat, Republican, Independent, etc.

– Attribute: Self-esteem

– Level: High, Medium, Low

INDEPENDENT VARIABLEINDEPENDENT VARIABLE

• the variable that is manipulated either by the researcher or by nature or circumstance (pp. 108-110)

• independent variables are also called “stimulus” “input” or “predictor” variables

• analogous to the “cause” in a cause-effect relationship

“operationalization” of the independent variable• Operationalization:

translating an abstract concept into a tangible, observable form in an experiment (pp. 178-179)

• Operationalizations can include:– variations in stimulus

conditions (public schools versus home schooling)

– variations in levels or degrees (mild vs. moderate vs. strong fear appeals)

– variations based on standardized scales or diagnostic instruments (low vs. high self esteem scores)

– variations in “intact” or “self-selected” groups (single parent vs. dual parent households)

TYPES OF VARIABLES

• Discrete variables– Nominal variables:

distinct, mutually exclusive categories (p. 111)

• religion; Buddhists, Christians, Jews, Muslims, etc.

• occupation; truck driver, teacher, engineer

• marital status; single, married, divorced

– Concrete versus abstract variables (p. 104)

• concrete; relatively fixed, unchanging

• biological sex

• ethnicity

• abstract; dynamic, transitory

• mood, emotion

• occupation

• social media use

varieties and types of variables--continued

– Dichotomous variables:

• true/false, female/male, democrat/republican

– Ordered variables: mutually exclusive categories, but with an order, sequence, or hierarchy (p. 111-112)

• fall, winter, summer, spring

• K-6, junior high, high school, college

• Continuous variables (interval and ratio): include constant increments or gradations, which can be arithmetically compared and contrasted (pp. 113-115)

– IQ scores

– self-esteem scores

– age

– heart rate, blood pressure

– frequency of touch

UNIT OF ANALYSIS

• Definition: The specific entity being examined (p. 105)– individual; self esteem,

fluency– dyad: self disclosure, touch – group: roles, norms– organization: communication

networks, upward-downward influence

– culture: individualism vs. collectivism

• What constitutes a specific score or measure on the outcome variable?– marital satisfaction?– one row of data in SPSS

• Ecological fallacy: drawing conclusions about individuals based on group data

• committing a “sweeping generalization” about participants in a research study– all Asians are collectivistic– all southerners are bigots– all Catholics oppose gay

marriage

OPERATIONALIZATION

• definition: the specific steps or procedures required to translate an abstract concept into a concrete, testable variable

– example: high versus low self-esteem (split-half or top vs. bottom third)

– example: on-line versus traditional classroom (the amount of online instruction that constitutes an “on-line” class)

examples of operationalizations

• credibility (high versus low)

• culture/ethnicity (self-report)

• type of speech therapy (in-clinic vs. at school, vs. at home)

• compliance-gaining strategy preferences (positive versus negative, self-benefit versus other benefit)

• “powerless” language style

• fear appeals (mild, moderate, strong)

• food server touch versus no touch

DEPENDENT VARIABLEDEPENDENT VARIABLE

• a variable that is observed or measured, and that is influenced or changed by the independent variable

• dependent variables are also known as “response” or “output” or “criterion” variables

• analogous to the “effect” in a cause-effect relationship

CONFOUNDING VARIABLECONFOUNDING VARIABLE

• also known as extraneous variables or intervening variables (p. 110, p. 267)

• confounding variables “muddy the waters”

• alternate causal factors or contributory factors which unintentionally influence the results of an experiment, but aren’t the subject of the study

MEDIATING VARIABLE

• a.k.a. moderating, intervening, intermediary, or mediating variables

• a 2nd or 3rd variable that can increase or decrease the relationship between an independent and a dependent variable.

• for example, whether listeners are persuaded more by the quality or quantity of arguments is moderated by their degree of involvement in an issue.

interchangeability of independent and dependent variables

• The same concept or construct could serve as the independent variable in one investigation, and the dependent in another.

• example: “source credibility”– as an independent variable; RQ: Does source credibility

(low versus high) have a significant effect on attitude change?

– As a dependent variable; RQ: Does the amount of evidence contained in a speech affect listeners’ perceptions of the source’s credibility?

• example: “fetal alcohol syndrome” (FAS)– As an independent variable: RQ: Does severity of FAS

correlate positively with language delay in infants?– As a dependent variable: RQ: Does the amount of

maternal alcohol use correlate positively with the severity of FAS in infancy?

RELATIONSHIPS AMONG VARIABLES

• Differences– Differences in kind, degree

• Relationships (correlations)– Positive correlation– Negative correlation– No or neutral correlation