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Trying to Discover Sufficient Condition Causes
Scientific human psychology is ultimately obligated to be able to describe, predict, and causally explain the psychological phenomena of every individual person. If all of this can be done in terms of the interrelations of linear combinations of variables, then our heavy reliance on statistical line...
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| Published in: | Methodology 2010, Vol.6 (2), p.59-70 |
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| Format: | Article |
| Language: | English |
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| cites | cdi_FETCH-LOGICAL-a363t-65cb0fff5cde9a205eeb8f6859cc2c80c61d7ad124febadbd337fb6a9530bc5e3 |
| container_end_page | 70 |
| container_issue | 2 |
| container_start_page | 59 |
| container_title | Methodology |
| container_volume | 6 |
| creator | Krause, Merton S |
| description | Scientific human psychology is ultimately obligated to be able to describe,
predict, and causally explain the psychological phenomena of every individual
person. If all of this can be done in terms of the interrelations of linear
combinations of variables, then our heavy reliance on statistical linear models
will have been justified. But can it? The rather imperfect fits of
such models to our data do not provide such justification, so perhaps more
fundamental forms of data representation would be prudent to look into, given
our modern computing capabilities. Such a form is offered in this paper:
point-to-point mappings from independent-variable to dependent-variable
hyperspaces. Its mathematical relationship to linear models is defined and
explains why linear models may often not be capable of fitting psychological
data. |
| doi_str_mv | 10.1027/1614-2241/a000007 |
| format | article |
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predict, and causally explain the psychological phenomena of every individual
person. If all of this can be done in terms of the interrelations of linear
combinations of variables, then our heavy reliance on statistical linear models
will have been justified. But can it? The rather imperfect fits of
such models to our data do not provide such justification, so perhaps more
fundamental forms of data representation would be prudent to look into, given
our modern computing capabilities. Such a form is offered in this paper:
point-to-point mappings from independent-variable to dependent-variable
hyperspaces. Its mathematical relationship to linear models is defined and
explains why linear models may often not be capable of fitting psychological
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predict, and causally explain the psychological phenomena of every individual
person. If all of this can be done in terms of the interrelations of linear
combinations of variables, then our heavy reliance on statistical linear models
will have been justified. But can it? The rather imperfect fits of
such models to our data do not provide such justification, so perhaps more
fundamental forms of data representation would be prudent to look into, given
our modern computing capabilities. Such a form is offered in this paper:
point-to-point mappings from independent-variable to dependent-variable
hyperspaces. Its mathematical relationship to linear models is defined and
explains why linear models may often not be capable of fitting psychological
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predict, and causally explain the psychological phenomena of every individual
person. If all of this can be done in terms of the interrelations of linear
combinations of variables, then our heavy reliance on statistical linear models
will have been justified. But can it? The rather imperfect fits of
such models to our data do not provide such justification, so perhaps more
fundamental forms of data representation would be prudent to look into, given
our modern computing capabilities. Such a form is offered in this paper:
point-to-point mappings from independent-variable to dependent-variable
hyperspaces. Its mathematical relationship to linear models is defined and
explains why linear models may often not be capable of fitting psychological
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| ispartof | Methodology, 2010, Vol.6 (2), p.59-70 |
| issn | 1614-1881 1614-2241 |
| language | eng |
| recordid | cdi_proquest_journals_614513040 |
| source | PsycARTICLES |
| subjects | Biological and medical sciences Fundamental and applied biological sciences. Psychology Mathematical Modeling Psychology Psychology. Psychoanalysis. Psychiatry Psychology. Psychophysiology Psychometrics. Statistics. Methodology Statistical Data Statistics. Mathematics |
| title | Trying to Discover Sufficient Condition Causes |
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