QUANTITATIVE THEORY USE (Before discussing quantitative theories)
Discussing quantitative theories
journalpapers.org - Before discussing
quantitative theories, it is important to understand variables and the types
that are used in forming theories. A variable refers to a characteristic
or attribute of an individual or an organization that can be measured or
observed and that varies among the people or organization being studied.
This variance means that scores in a given situation fall into at least two mutually exclusive categories (Thompson, 2006). Psychologists prefer to use the term construct (rather than variable), which carries the connotation more of an abstract idea than a specifically defined term.
However, social scientists typically use the term variable, and it will be employed in this discussion. Variables often measured in studies include gender: age: socioeconomic status (SES): and attitudes or behaviors such as racism, social control, political power, or leadership.
Several texts provide detailed discussions about the types of variables one can use and their scales of measurement (e.g., Isaac & Michael, 1981; Keppel, 1991; Kerlinger, 1979; Thompson, 2006; Thorndike, 1997). Variables are distin¬guished by two characteristics: (a) temporal order and (b) their measure¬ment (or observation).
Temporal order means that one variable precedes another in time. Because of this time ordering, it is said that one variable affects or causes another variable: though a more accurate statement would be that one variable probably causes another.
When dealing with studies in the natu¬ral setting and with humans, researchers cannot absolutely prove cause and effect (Rosenthal & Rosnow, 1991), and social scientists now say that there is “probable causation”
Temporal order means that quantitative researchers think about variables in order from “left to right" (Punch, 2005) and order the variables in purpose statements, research questions, and visual models into the left-to-right, cause-and-effect type presentations.
Thus, see the following:
1. Independent
variables are those that (probably) cause, influence, or latest outcomes. They hey
are also called treatment, manipulated, antecedent, or predictor variables.
2. Dependent
variables are those that depend on the independent vari¬ables, they are the
outcomes or results of the influence of the independent variables. Other names
for dependent variables are criterion, outcome, effect, and response variables.
3. Intervening
or mediating variables stand between the independent and dependent variables,
and they mediate the effects of the independent variables on the dependent
variable. For example, if students do well on a research methods test
(dependent variable), results may be due to (a) their study preparation (independent variable)
and/or (b) their organization of study ideas into a framework (intervening
variable) that influenced their performance on the test. The mediating
variable, the organization of study, stands between the independent and
dependent variables in the probable causal link.
4. Moderating variables are independent variables that affect the direction
and/or the strength of the relationship between independent and dependent
variables (Thompson, 2006). These moderating variables are new variables
constructed by a researcher by taking one variable and multiplying it by
another to determine the joint impact of both on the dependent variable (e.g.,
age X attitudes toward quality of life-impacting self-esteem). These variables
are typically found in experiments.
5. Two other types of
variables are control variables and confounding variables. Control variables play an active role in quantitative studies.
These are a special type of independent variable that researchers measure
because they potentially influence the dependent variable.
Researchers
use statistical procedures (e.g., analysis of covariance [ANCOVA]) to control
for these variables. They may be demographic or personal variables (e.g., age
or gender) that need to be “controlled” so that the true influence of the independent
variable on the dependent can be determined.
Another
type of variable, a confounding (or spurious) variable, is not actually measured
or observed in a study. It exists, but its influence cannot be directly
detected. Researchers comment on the influence of confounding variables after
the study has been completed, because these variables may have operated to
explain the relationship between the independent variable and dependent
variable, but they were not or could not be easily assessed (e.g., a confounding
variable such as discriminatory attitudes).
In the quantitative research study, variables are related to answering a research
question (e.g., “How does self-esteem influence the formation of friendships
among adolescents?") or to make predictions about what the researcher
expects the results to show. These predictions are called hypotheses "Individual positive self-esteem expands the number of trends of
adolescents.”)
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