Research Design

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Research Design
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What is Research Design ?

• Plan for getting from the research question to
  the conclusion
• Blueprint for data collection and interpretation
• Deals with the logic of scientific inquiry
• A strategy for testing hypothesis
• Interpretative work
• Understanding phenomenon
• A plan for conducting scientific research for the
  purpose of learning about a phenomenon of interest

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What is Research Design ?

• Overall plan or framework for the investigation,
  anticipate all of the subsequent stages of the
  research process.
• Decision also be made for
• Selecting unit of analysis
• Selecting variable to observed and controlled
• How to measured variables
• How to analyze of data
• Good Research Design should rule-out alternative
  explanations

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Alternative Explanations

• Asian financial crisis in the late 1990s
• Institutional weaknesses (lack of transparency in
  corporate and political governance) -gt cronyism
• Market failure with under-regulation of financial
  market

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Unit of Analysis

• The entity about whom or which the researcher
  gathers information.
• The unit is simply what or who to be described or
  analyzed
• Examples of unit
• Individuals
• Groups
• Artifacts (books, photos, newspapers)
• Geographical units (town, census tract, state)
• Social interactions (dyadic relations, divorces,
  arrests)

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Units of Analysis Examples

• If you are comparing the children in two
  classrooms on achievement test scores, the unit
  is the individual child because you have a score
  for each child.
• On the other hand, if you are comparing the two
  classes on classroom climate, your unit of
  analysis is the group, in this case the
  classroom, because you only have a classroom
  climate score for the class as a whole and not
  for each individual student.

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Units of Analysis Examples (2)

• If the researcher wanted to know what kind of
  people are attracted to the field of computer
  science, the unit is individual people
• If the researcher wanting to determine if larger
  organization have more bureaucratic rules and
  regulations, the unit is organization

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Hierarchical Modeling

• The incorporation of multiple units of analysis
  within a single analytic model
• Aggregation in the analysis
• Analyze individual person using aggregate data to
  characterize the groups or collectivities to
  which the individuals belong.
• For instance, in an educational study, you might
  want to compare student performance with teacher
  expectations. To examine this relationship would
  require averaging student performance for each
  class because each teacher has multiple students
  and you are collecting data at both the teacher
  and student level.

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Fallacy

• An error in reasoning, usually based on mistaken
  assumptions.
• Ecological fallacy
• Exception falalcy

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Ecological Fallacy

• Occurs when you make conclusions about
  individuals based only on analyses of group data.
  
• For instance, assume that you measured the math
  scores of a particular classroom and found that
  they had the highest average score in the
  district. Later (probably at the mall) you run
  into one of the kids from that class and you
  think to yourself, 'She must be a math whiz.'
  Aha! Fallacy! Just because she comes from the
  class with the highest average doesn't mean that
  she is automatically a high-scorer in math. She
  could be the lowest math scorer in a class that
  otherwise consists of math geniuses.

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Exception fallacy

• Sort of the reverse of the ecological fallacy.
• It occurs when you reach a group conclusion on
  the basis of exceptional cases.
• The stereotype is of the guy who sees a woman
  make a driving error and concludes that women are
  terrible drivers. Wrong! Fallacy!

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Variables

• Any entity that can take on different values
• Characteristics of units that vary, taking on
  different values, categories, or attributes for
  different observations
• May vary over cases, over time or over both cases
  and time
• Example
• Age (range of years)
• Gender (female male)
• Marital status (single, married, divorced,
  widowed, etc)
• Level of education (primary, secondary, diploma,
  etc)

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Types of variables

• Explanatory
• Dependent variables
• Independent variables
• Antecedent variables
• Intervening variables
• Extraneous
• Controlled
• Uncontrollled
• Qualitative Quantitative

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Dependent-Independent

• Dependent is variables that the researcher
  interested in explaining or describing
• Independent is the explanatory variables that do
  the influencing and explaining, also called
  predictor variable
• In terms of cause and effect, the independent
  variable is the presumed cause and the dependent
  variable is the presumed effect
• For example when the relationship between
  educational attainment (years of schooling) and
  income is studied, educational attainment is the
  IV and income is DV

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Antecedent intervening

• Antecedent variable occurs prior in time to both
  the independent and dependent variable
• Intervening variable occurs if it is an effect of
  the independent variable and a cause of the
  dependent variable

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Quantitative Qualitative

• A variable is quantitative if its value or
  categories consist of numbers and if differences
  between its categories can be expressed
  numerically
• Income
• Qualitative variables have discrete categories,
  usually designated by words or labels, and
  nonnumerical differences between categories
• Gender ? male female

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RQ, Unit analysis and variables
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Relationship

• Types of relationship
• Among Qualitative variables
• Among Quantitative variables
• Between Qualitative and Quantitative variables
• Properties of relationship
• The extent of to which variables are associated
  or correlated
• Strength
• How changes in one variable are related to
  changes in another
• Directionality
• Linearity

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Relationship among qualitative variables
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Relationship among quantitative variables

• Direction and linearity
• Direction ? positive vs negative
• Linearity ? linear vs curvilinear
• A positive (direct relationship) between
  variables exists if an increase in the value of
  one variable is accompanied by an increase in the
  value of the other, or if a decrease in the value
  of one variable is accompanied by a decrease in
  the value of the other.
• Sons heights and fathers heights (the taller
  the father, the taller the son will tend to be)
• A negative (inverse relationship) between
  variables exists if a decrease in the value of
  one variable is accompanied by increase in the
  value of the other.
• Speed and accuracy (the faster one does
  something, the less accuracy one is likely to do
  it)

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Relationship among quantitative variables (2)
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Relationship between qualitative and quantitative
variables