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Indirect tests of memory
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Indirect tests of memory
Indirect memory tests assess the retention of information without direct reference to the source of information. Participants are given tasks designed to elicit knowledge that was acquired incidentally or unconsciously and is evident when performance shows greater inclination towards items initially presented than new items. Performance on indirect tests may reflect contributions of implicit memory, the effects of priming, a preference to respond to previously experienced stimuli over novel stimuli. Types of indirect memory tests include the implicit association test, the lexical decision task, the word stem completion task, artificial grammar learning, word fragment completion, and the serial reaction time task.
The implicit association test is a testing method designed by Anthony Greenwald, Debbie McGhee and Jordan Schwartz, and was first introduced in 1998. The IAT measures the associative strength between categories (e.g. Bug, Flower) and attributes (e.g. Bad, Good) by having participants rapidly classify stimuli that represent the categories and attributes of interest on a computer. During four of the seven trial blocks in an IAT, categories and attributes share a response key (e.g. Bug or Bad, Flower or Good), with the underlying assumption being that participant response times will be quicker when the category and attribute are more closely associated.
The first two trial blocks have participants match stimuli only to categories or attributes, to allow participants to practice grouping the stimuli (Bug, Flower). The third and fourth trial blocks mark the first occurrence that a category and attribute share a response key, and during these blocks, categories and attributes are grouped in a congruently associative manner (e.g. Bug with Bad, Flower with Good). The fifth trial block has the category labels switch sides, and gives participants a chance to practice grouping stimuli from the category, with the new orientation of the labels (e.g. Flower, Bug). Finally, the sixth and seventh trial blocks have categories and attributes sharing a response key again, but now, because of the switching of sides for the category, labels are now presented in an incongruently associative manner (Flower and Bad, Bug and Good).
Originally, a participant's performance during an IAT was scored in milliseconds, depending on how much time they took to respond each trial, but since then, an improved scoring algorithm has been created. The resulting "D measure" was found to be superior in a variety of ways, such as creating larger correlations with explicit measures, and reducing the effects of prior IAT experience. Interpreting the D measure is also fairly straightforward, with high positive scores indicating a congruent implicit preference, high negative scores indicating an incongruent implicit preference, and scores around zero indicating a relatively neutral implicit preference.
Implicit measures, especially latency-based ones, typically struggle to achieve a satisfactory level of internal consistency and test-retest reliability. However, the IAT possess acceptable levels of both, with one review finding that internal consistency values of IAT's typically ranged from .7 to .9. In terms of test-retest reliability, the IAT has shown itself to be a relatively stable measure, however, little research has examined the test-retest reliability of the IAT with a gap in time larger than a month between administrations.
The IAT has also established itself to be an acceptably valid measure, and has demonstrated this through its convergent validity, discriminant validity, and predictive validity. The IAT's convergent and discriminant validity has been established through its comparison with explicit measures, whereby IAT's were found to relate to explicit measures targeting the traits, and not with explicit measures targeting unrelated traits. Additionally, multitrait-multimethod studies have demonstrated that although IATs and explicit measures may be related, they appear to be measuring different constructs. Overall, the IAT has been found to be an effective predictor of behavior, and is generally superior to self-report measures when dealing with topics of discrimination and stereotyping, especially when examining patterns of ingroup liking (e.g. preferring Canadians over Americans if one is Canadian, and vice versa if one is American).
The IAT is a procedure applied to a variety of research topics, including examinations of self-esteem, consumer studies, and human sexuality. Often, it is the IAT's ability to skirt socially desirable response biases that makes it an attractive method, and it is often used in lieu of, or alongside explicit self-report measures.
Implicit self-esteem IAT's utilize "self" and "other" as categories, and "positive" and "negative" as attributes. Participants who group "self" stimuli quicker when sharing a response with "positive" stimuli show positive implicit self-esteem. On the other hand, participants who group "self" stimuli quicker when sharing a response key with "negative" stimuli show low implicit self-esteem. In one implicit self-esteem IAT study, it was demonstrated that North American and Asian university students all have relatively high levels of implicit self-esteem. This is quite a difference when compared with explicit measures of self-esteem, as North American participants tended to have much higher levels of explicit self-esteem than their Asian counterparts, highlighting implicit self-esteem as a possibly universal phenomenon. Separate research examining the relationship of implicit and explicit self-esteem has determined that the two are separate, but weakly related constructs.
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Indirect tests of memory
Indirect memory tests assess the retention of information without direct reference to the source of information. Participants are given tasks designed to elicit knowledge that was acquired incidentally or unconsciously and is evident when performance shows greater inclination towards items initially presented than new items. Performance on indirect tests may reflect contributions of implicit memory, the effects of priming, a preference to respond to previously experienced stimuli over novel stimuli. Types of indirect memory tests include the implicit association test, the lexical decision task, the word stem completion task, artificial grammar learning, word fragment completion, and the serial reaction time task.
The implicit association test is a testing method designed by Anthony Greenwald, Debbie McGhee and Jordan Schwartz, and was first introduced in 1998. The IAT measures the associative strength between categories (e.g. Bug, Flower) and attributes (e.g. Bad, Good) by having participants rapidly classify stimuli that represent the categories and attributes of interest on a computer. During four of the seven trial blocks in an IAT, categories and attributes share a response key (e.g. Bug or Bad, Flower or Good), with the underlying assumption being that participant response times will be quicker when the category and attribute are more closely associated.
The first two trial blocks have participants match stimuli only to categories or attributes, to allow participants to practice grouping the stimuli (Bug, Flower). The third and fourth trial blocks mark the first occurrence that a category and attribute share a response key, and during these blocks, categories and attributes are grouped in a congruently associative manner (e.g. Bug with Bad, Flower with Good). The fifth trial block has the category labels switch sides, and gives participants a chance to practice grouping stimuli from the category, with the new orientation of the labels (e.g. Flower, Bug). Finally, the sixth and seventh trial blocks have categories and attributes sharing a response key again, but now, because of the switching of sides for the category, labels are now presented in an incongruently associative manner (Flower and Bad, Bug and Good).
Originally, a participant's performance during an IAT was scored in milliseconds, depending on how much time they took to respond each trial, but since then, an improved scoring algorithm has been created. The resulting "D measure" was found to be superior in a variety of ways, such as creating larger correlations with explicit measures, and reducing the effects of prior IAT experience. Interpreting the D measure is also fairly straightforward, with high positive scores indicating a congruent implicit preference, high negative scores indicating an incongruent implicit preference, and scores around zero indicating a relatively neutral implicit preference.
Implicit measures, especially latency-based ones, typically struggle to achieve a satisfactory level of internal consistency and test-retest reliability. However, the IAT possess acceptable levels of both, with one review finding that internal consistency values of IAT's typically ranged from .7 to .9. In terms of test-retest reliability, the IAT has shown itself to be a relatively stable measure, however, little research has examined the test-retest reliability of the IAT with a gap in time larger than a month between administrations.
The IAT has also established itself to be an acceptably valid measure, and has demonstrated this through its convergent validity, discriminant validity, and predictive validity. The IAT's convergent and discriminant validity has been established through its comparison with explicit measures, whereby IAT's were found to relate to explicit measures targeting the traits, and not with explicit measures targeting unrelated traits. Additionally, multitrait-multimethod studies have demonstrated that although IATs and explicit measures may be related, they appear to be measuring different constructs. Overall, the IAT has been found to be an effective predictor of behavior, and is generally superior to self-report measures when dealing with topics of discrimination and stereotyping, especially when examining patterns of ingroup liking (e.g. preferring Canadians over Americans if one is Canadian, and vice versa if one is American).
The IAT is a procedure applied to a variety of research topics, including examinations of self-esteem, consumer studies, and human sexuality. Often, it is the IAT's ability to skirt socially desirable response biases that makes it an attractive method, and it is often used in lieu of, or alongside explicit self-report measures.
Implicit self-esteem IAT's utilize "self" and "other" as categories, and "positive" and "negative" as attributes. Participants who group "self" stimuli quicker when sharing a response with "positive" stimuli show positive implicit self-esteem. On the other hand, participants who group "self" stimuli quicker when sharing a response key with "negative" stimuli show low implicit self-esteem. In one implicit self-esteem IAT study, it was demonstrated that North American and Asian university students all have relatively high levels of implicit self-esteem. This is quite a difference when compared with explicit measures of self-esteem, as North American participants tended to have much higher levels of explicit self-esteem than their Asian counterparts, highlighting implicit self-esteem as a possibly universal phenomenon. Separate research examining the relationship of implicit and explicit self-esteem has determined that the two are separate, but weakly related constructs.