Natural Group Design
Individual differences variables (or subject variables) are selected rather
than manipulated to form natural groups designs.
• The natural groups design represents a type of correlational research in
which researchers look for covariations between natural groups variables and dependent variables.
• Causal inferences cannot be made regarding the effects of natural groups
variables because plausible alternative explanations for group differences exist.
Researchers in many areas of psychology are interested in independent vari- ables that are called individual differences variables, or subject variables. An individual differences variable is a characteristic or trait that varies across in- dividuals. Religious affiliation is an example of an individual differences vari- able. Researchers can’t manipulate this variable by randomly assigning people to Catholic, Jewish, Muslim, Protestant, or other groups. Instead, researchers “control” the religious affiliation variable by systematically selecting individu- als who naturally belong to these groups. Individual differences variables such as gender, introversion–extraversion, race, or age are important independent variables in many areas of psychology.
It is important to differentiate experiments involving independent variables whose levels are selected from those involving independent variables whose levels are manipulated. Experiments involving independent variables whose levels are selected—like individual differences variables—are called natural groups designs. The natural groups design is frequently used in situations in which ethi- cal and practical constraints prevent us from directly manipulating independent variables. For example, no matter how interested we might be in the effects of major surgery on subsequent depression, we could not ethically perform major surgery on a randomly assigned group of introductory psychology students and then compare their depression symptoms with those of another group who did not receive surgery! Similarly, if we were interested in the relationship between divorce and emotional disorders, we could not randomly assign some people to get divorced. By using the natural groups design, however, we can compare people who have had surgery with those who have not. Similarly, people who have chosen to divorce can be compared with those who have chosen to stay married.
Researchers use natural groups designs to meet the first two objectives of the scientific method: description and prediction. For example, studies have shown that people who are separated or divorced are much more likely to receive psychiatric care than are those who are married, widowed, or have remained single. On the basis of studies like these, we can describe divorced and married individuals in terms of emotional disorders, and we can predict which group is more likely to experience emotional disorders.
Serious problems can arise, though, when the results of natural groups designs are used to make causal statements. For instance, the finding that divorced persons are more likely than married persons to receive psychiatric care shows that these two factors covary. This finding could be taken to mean that divorce causes emotional disorders. But, before we conclude that divorce causes emotional disorders, we must assure ourselves that the time-order con- dition for a causal inference has been met. Does divorce precede the emotional disorder, or does the emotional disorder precede the divorce? A natural groups design does not tell us.
The natural groups design also poses problems when we try to satisfy the third condition for demonstrating causality, eliminating plausible alterna- tive causes. The individual differences studied in the natural groups design are usually confounded—groups of individuals are likely to differ in many ways in addition to the variable used to classify them. For example, individu- als who divorce and individuals who stay married may differ with respect to a number of characteristics other than their marital status, for example, their religious practices or financial circumstances. Any differences observed between divorced and married individuals may be due to these other char- acteristics, not to divorce. The manipulation done by “nature” is rarely the controlled type we have come to expect in establishing the internal validity of an experiment.
There are approaches for drawing causal inferences in the natural groups design. One effective approach requires that individual differences be stud- ied in combination with independent variables that can be manipulated. This combination of more than one independent variable in one experiment requires the use of a complex design, which we will describe in Chapter 8. For now, rec- ognize that drawing causal inferences based on the natural groups design can be a treacherous enterprise. Although such designs are sometimes referred to as “experiments,” there are important differences between an experiment involving an individual differences variable and an experiment involving a manipulated variable.
combination of more than one independent variable in one experiment requires the use of a complex design, which we will describe in Chapter 8. For now, rec- ognize that drawing causal inferences based on the natural groups design can be a treacherous enterprise. Although such designs are sometimes referred to as “experiments,” there are important differences between an experiment involving an individual differences variable and an experiment involving a manipulated variable.
Individual differences variables (or subject variables) are selected rather
than manipulated to form natural groups designs.
• The natural groups design represents a type of correlational research in
which researchers look for covariations between natural groups variables and dependent variables.
• Causal inferences cannot be made regarding the effects of natural groups
variables because plausible alternative explanations for group differences exist.
Researchers in many areas of psychology are interested in independent vari- ables that are called individual differences variables, or subject variables. An individual differences variable is a characteristic or trait that varies across in- dividuals. Religious affiliation is an example of an individual differences vari- able. Researchers can’t manipulate this variable by randomly assigning people to Catholic, Jewish, Muslim, Protestant, or other groups. Instead, researchers “control” the religious affiliation variable by systematically selecting individu- als who naturally belong to these groups. Individual differences variables such as gender, introversion–extraversion, race, or age are important independent variables in many areas of psychology.
It is important to differentiate experiments involving independent variables whose levels are selected from those involving independent variables whose levels are manipulated. Experiments involving independent variables whose levels are selected—like individual differences variables—are called natural groups designs. The natural groups design is frequently used in situations in which ethi- cal and practical constraints prevent us from directly manipulating independent variables. For example, no matter how interested we might be in the effects of major surgery on subsequent depression, we could not ethically perform major surgery on a randomly assigned group of introductory psychology students and then compare their depression symptoms with those of another group who did not receive surgery! Similarly, if we were interested in the relationship between divorce and emotional disorders, we could not randomly assign some people to get divorced. By using the natural groups design, however, we can compare people who have had surgery with those who have not. Similarly, people who have chosen to divorce can be compared with those who have chosen to stay married.
Researchers use natural groups designs to meet the first two objectives of the scientific method: description and prediction. For example, studies have shown that people who are separated or divorced are much more likely to receive psychiatric care than are those who are married, widowed, or have remained single. On the basis of studies like these, we can describe divorced and married individuals in terms of emotional disorders, and we can predict which group is more likely to experience emotional disorders.
Serious problems can arise, though, when the results of natural groups designs are used to make causal statements. For instance, the finding that divorced persons are more likely than married persons to receive psychiatric care shows that these two factors covary. This finding could be taken to mean that divorce causes emotional disorders. But, before we conclude that divorce causes emotional disorders, we must assure ourselves that the time-order con- dition for a causal inference has been met. Does divorce precede the emotional disorder, or does the emotional disorder precede the divorce? A natural groups design does not tell us.
The natural groups design also poses problems when we try to satisfy the third condition for demonstrating causality, eliminating plausible alterna- tive causes. The individual differences studied in the natural groups design are usually confounded—groups of individuals are likely to differ in many ways in addition to the variable used to classify them. For example, individu- als who divorce and individuals who stay married may differ with respect to a number of characteristics other than their marital status, for example, their religious practices or financial circumstances. Any differences observed between divorced and married individuals may be due to these other char- acteristics, not to divorce. The manipulation done by “nature” is rarely the controlled type we have come to expect in establishing the internal validity of an experiment.
There are approaches for drawing causal inferences in the natural groups design. One effective approach requires that individual differences be stud- ied in combination with independent variables that can be manipulated. This combination of more than one independent variable in one experiment requires the use of a complex design, which we will describe in Chapter 8. For now, rec- ognize that drawing causal inferences based on the natural groups design can be a treacherous enterprise. Although such designs are sometimes referred to as “experiments,” there are important differences between an experiment involving an individual differences variable and an experiment involving a manipulated variable.
combination of more than one independent variable in one experiment requires the use of a complex design, which we will describe in Chapter 8. For now, rec- ognize that drawing causal inferences based on the natural groups design can be a treacherous enterprise. Although such designs are sometimes referred to as “experiments,” there are important differences between an experiment involving an individual differences variable and an experiment involving a manipulated variable.
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