Chapter 5

• Causal modeling


  Creating and testing models that may suggest cause-and-effect relationships among behaviors.
• Coefficient of determination (r2)

  In a correlational study, an estimate of the amount of variability in scores on one variable that can be explained by the other variable.
• Correlation

  The degree of relationship between two variables such as traits, behaviors, or events, represented by r.
• Correlational study


  A study designed to determine the correlation between two traits, behaviors, or events.
• Cross-lagged panel design

  • A method in which the same set of behaviors or characteristics are measured at two separate points in time (often years apart).
  • Six different correlations are computed, and the pattern of correlations is used to infer the causal direction.
• Cross-sectional study

  • A method in which different groups of subjects who are at different stages are measured at a single point in time.
  • A method that looks for time-related changes.
  • Investigates changes across time by comparing groups of subjects already at different stages at a single point in time.
• Ex post facto study

  A study in which a researcher systematically examines the effects of preexisting subject characteristics (often called subject variables) by forming groups based on these naturally occuring differences between subjects.

  
  

  Explores characteristics, behaviors, or effects of naturally occurring events in preexisting groups of subjects.
• Linear regression analysis

  A correlation-based method for estimating a score on one measured behavior from a score on the other when two behaviors are strongly related.
• Longitudinal design

  • A method in which the same group of subjects is followed and measured at different points in time.
  • A method that looks for change across time.
  • Investigates changes across time by measuring behavior of same group of subjects at different points in time.
• Multiple correlation

  Statistical intercorrelations among three or more variables or behaviors, represented by R.
• Multiple regression analysis

  A correlation-based technique (from multiple correlation) that uses a regression equation to predict the score on one behavior from scores on the other related behaviors or on sets of other variables.
• Negative correlation

  • The relationship existing between two variables such that an increase in one is associated with a decrease in the other.
  • Also called an inverse relationship.
• Partial correlation

  An analysis that allows the statistical influence of one measure variable to be held constant while computing the correlation between the other two measured variables.

  Uses beta weights from multiple regression analysis to generate possible direction of cause and effect from correlated variables.
• Path analysis

  • An important correlation-based method in which subjects are measured on several related behaviors.
  • The researcher creates (and tests) models of possible causal sequences using sophisticated correlational techniques.
• Positive correlation

  • The relationship between two measures such that an increase in the value of one associated with an increase in the value of the other.
  • Also called a direct relationship.
• Pretest/posttest design

  • A research design used assess whether the occurrence of an event alters behavior.
  • Scores from measurements made before and after the event (called the pretest and posttest) are compared.
  • Explores the effects of an event (or treatment) by comparing behavior before and after the event (or treatment).
• Quasi-experiment designs

  Often seem like (as they prefix quasi- implies) real experiments, but they lack one or more of its essential elements, such as manipulation of antecedents and random assignment to treatment conditions.

  
  

  Investigates differences in preexisting groups of subjects; group differences on some variable may be explored or different treatments given to preexisting groups may be compared.
• Regression line

  • The line of best fit.
  • Represents the equation that best describes the mathematical relationship between two variables measured in a correlational study.
• Scatterplot

  • A graph of data from a correlational study, created by plotting pairs of scores from each subject.
  • The value of one variable is plotted on the X (horizontal) axis and the other variable on the Y (vertical) axis.
• Simple correlations

  Relationships between pairs of scores from each subject.
• Subject variable

  • The characteristics of the subjects in an experiment or quasi-experiment that cannot be manipulated by the researcher.
  • Sometimes used to select subject into groups.
• Subject variable

  1. The characteristics of the subjects in an experiment or quasi-experiment that cannot be manipulated by the researcher.
  2. Sometimes used to select subjects into groups.
• Factor analysis


  Determines subsets of correlated variables within a larger set of variables.
• Nonequivalent groups design


  A design in which the researcher compares the effects of different treatment conditions on preexisting groups of participants.

  Compares the effects of different treatment conditions on preexisting groups of subjects.