Methodological Approach and Key Distinctions

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Methodological Approach and Key Distinctions
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Key Methodological Approaches

• The positivist approach
• The interpretive approach

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Characteristics of Positivist Approach

• Predominantly quantitative
• Advocate an objective approach
• Emphasis on having reliable knowledge can make
  predictions

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Positivism Assumptions

• All behaviour is naturally determined
• Humans are part of the natural world
• Nature is orderly and regular
• All objective phenomena are eventually knowable
• Nothing is self-evident
• Truth is relative
• Knowledge comes from experience

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Positivism Research Designs

• Quantitative methods of data collection
• Illustrate patterns of behaviour using
  statistical terms
• Predict the relationship among variables
• Common methods of data collection
• Experiments, surveys, secondary data analysis

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Criticisms of Positivism

• Value-free goal is unattainable
• Subjective element missed how people shape the
  psychological experience

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Interpretive Approach

• Max Weber (1864-1920) placed importance on
  peoples understanding of their actions
• To understand patterns requires empathetic or
  interpretative understanding Verstehen
• Emphasis on how people make sense of their lives
  and how their sense of self develops in
  interaction with others

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Interpretative Approach Assumptions

• Reject the positivist notion that people are
  completely shaped by outside factors
• Assumes behaviour is influenced by the meanings
  people attach to events and actions

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Interpretive Approach Research Designs

• Data collection and data analysis are cyclical,
  connected activities (see Chapter 6)
• Typical methods of data collection
• Participant observation
• In-depth interviews
• Focus groups

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Criticisms of the Interpretive Approach

• Over-emphasis on subjectivity
• Replication problem
• Knowing more and more about less and less

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Some Important Distinctions

• Quantitative versus qualitative research
• Descriptive versus explanatory research
• Pure versus applied research
• Units of analysis individuals/aggregations

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Quantitative Versus Qualitative Research

• Quantitative Research
• Use numbers, statistics, emphasis on measurement,
  precision, prediction
• Qualitative Research
• Emphasis on verbal descriptions
• Reflect the world as seen by the participant
• Focus on the lived experience of participant
• Use word-for-word quotations when reporting
  findings
• Typically employs small samples

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Descriptive Versus Explanatory

• Descriptive goal is to describe some aspect of
  society
• Census - description of entire population
• Sample - a small portion of the population who
  are selected to represent the population
• E.g., what are the differences in reaction time
  between participants given 1 oz of alcohol vs. 3
  oz of alcohol
• Explanatory goal is to explain relationships
• E.g., Why is it that some individuals can consume
  larger amounts of alcohol and not have as great a
  degree of impairment as others?
• Test alternative explanations

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Pure Versus Applied Research

• Pure Research tries to produce an understanding
  of patterns of behavior
• e.g. Cognitive psychologists try to explain
  what happens in our brain when we read.
• Applied Research tries to solve a problem or
  bring about certain changes in society
• e.g. Educational psychologists try to develop
  better reading instruction programs to increase
  literacy rates.

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Units of Analysis

• Individual level data that describe the
  attitudes or characteristics of individuals
• Aggregate level data that describe a
  characteristics of a group, community, or nation

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Variables Examples
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Kinds of Variables

• Quantitative (Ordinal, Interval, Ratio)
• Differences in amount
• Can be continuous or discrete
• Qualitative (Nominal)
• Differences in kind or category

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Continuous vs. Discrete Quantitative Variables

• Continuous
• Score can fall anywhere on a continuum
• Infinite number of values possible
• Discrete
• Measured in whole units
• No values between those units

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Types of Variables

• Dependent variables
• Independent variables (also called the treatment
  variable in experimental design)
• Control variables
• Extraneous variables
• Confounding variables

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Dependent Variable

• The variable being explained
• The measured variable
• The effect in the cause/effect relationship
• E.g., a study examining factors explaining why
  females choose gender-traditional versus
  non-traditional programs
• Dependent variable program of study
• Indicated as the letter Y
• X ? Y

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Independent Variable

• The cause in a cause-effect relationship
• The manipulated variable
• Indicated as the letter X in a formal statement
• X ? Y

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Quasi-Independent Variable

• The presumed cause in a relationship
• Cannot be manipulated
• Indicated as the letter X in a formal statement
• X ? Y

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Control Variables

• A control variable is a variable taken into
  account when exploring the relation between two
  variables
• Goal Control for the effects of other factors
• Three types of control variables
• Intervening/Mediating
• Extraneous
• Source of spuriousness/confounding

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A. Intervening Variable

• An intervening variable links an independent
  variable (X) to a dependent variable (Y)
• Thus, a change in X causes a change in I, which
  in turn causes a change in Y.
• gt X ? gt I ? gt Y
• Example Exposure to women who have
  non-traditional careers intervenes to explain
  why those of higher SES are more likely to choose
  nontraditional program of study

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B. Extraneous Variable

• A extraneous variable is a variable that accounts
  for some variability in the measurement of the
  dependent variable but does so in an unsystematic
  way
• E.g. Some people consume caffeine. Others do
  not.
• The effects may be the same in all groups or at
  all levels of the independent variable.

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C. Source of Spuriousness/ Confounding Variable

• A source of spuriousness variable is a variable
  that is viewed as having a possible influence on
  both the independent (X) and dependent (Y)
  variable, in such as way that it accounts for the
  relationship between them.
• Called a confounding variable in experimental
  research found to be systematically influencing
  the experiments outcome
• All individuals in one condition or group are
  affected by this variable.

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Source of Spuriousness/ Confounding (contd)

• Example When exploring the relationship between
  socioeconomic background and choice of
  nontraditional program by female students,
  consider the possibility that rural/urban
  background is the source of spuriousness.
• Does coming from a urban vs. rural background
  influence parents socioeconomic status as well
  as university program preferences

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Exercise

• Identify the variables in the following
  statements (independent, dependent, extraneous)
  
• We feel that the effect of school quality on
  academic achievement found in prior research is
  spurious because researchers have not examined
  the social class level of the students studied.
• When pay rate was held constant, we found no
  influence of job satisfaction on productivity.
• Serif's camp studies demonstrated that conflict
  between groups increases cohesion within groups.