P. Jonason, Phillip S. Kavanagh, Gregory D. Webster, Debra Fitzgerald
Could measurement level be a factor worth considering when studying the Dark Triad (i.e., narcissism, psychopathy, and Machiavellianism)? In two studies (N = 465), we compared the relative fit of two Dark Triad models: one that treats the three measures as separate-yet-related personality traits and another that treats the measures as tapping a single, latent construct. Mid-level personality traits, such as mate-retention strategies (Study 1) were best explained by a three-measure model, whereas the higher-order trait of sociosexuality (Study 2), were best explained by a single, latent-factor model. When considering mid-level measurement in personality, the three traits may provide independent effects for interpersonal relationships, whereas at the higher-order level, the three traits may function as a single entity relating to other higher-order traits. We suggest one should consider level of measurement between the predictor and criterion variables to better predict correlations among variables such as the Dark Triad.
{"title":"Comparing the Measured and Latent Dark Triad: Are Three Measures Better than One?","authors":"P. Jonason, Phillip S. Kavanagh, Gregory D. Webster, Debra Fitzgerald","doi":"10.2458/JMM.V2I1.12363","DOIUrl":"https://doi.org/10.2458/JMM.V2I1.12363","url":null,"abstract":"Could measurement level be a factor worth considering when studying the Dark Triad (i.e., narcissism, psychopathy, and Machiavellianism)? In two studies (N = 465), we compared the relative fit of two Dark Triad models: one that treats the three measures as separate-yet-related personality traits and another that treats the measures as tapping a single, latent construct. Mid-level personality traits, such as mate-retention strategies (Study 1) were best explained by a three-measure model, whereas the higher-order trait of sociosexuality (Study 2), were best explained by a single, latent-factor model. When considering mid-level measurement in personality, the three traits may provide independent effects for interpersonal relationships, whereas at the higher-order level, the three traits may function as a single entity relating to other higher-order traits. We suggest one should consider level of measurement between the predictor and criterion variables to better predict correlations among variables such as the Dark Triad.","PeriodicalId":90602,"journal":{"name":"Journal of methods and measurement in the social sciences","volume":"2 1","pages":"28-44"},"PeriodicalIF":0.0,"publicationDate":"2011-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"69054699","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Non-zero correlation coefficients have non-normal distributions, affecting both means and standard deviations. Previous research suggests that z transformation may effectively correct mean bias for N's less than 30. In this study, simulations with small (20 and 30) and large (50 and 100) N's found that mean bias adjustments for larger N's are seldom needed. However, z transformations improved confidence intervals even for N = 100. The improvement was not in the estimated standard errors so much as in the asymmetrical CI's estimates based upon the z transformation. The resulting observed probabilities were generally accurate to within 1 point in the first non-zero digit. These issues are an order of magnitude less important for accuracy than design issues influencing the accuracy of the results, such as reliability, restriction of range, and N. DOI:10.2458/azu_jmmss_v1i2_gorsuch
{"title":"Correlation Coefficients: Mean Bias and Confidence Interval Distortions","authors":"R. Gorsuch, C. Lehmann","doi":"10.2458/JMM.V1I2.114","DOIUrl":"https://doi.org/10.2458/JMM.V1I2.114","url":null,"abstract":"Non-zero correlation coefficients have non-normal distributions, affecting both means and standard deviations. Previous research suggests that z transformation may effectively correct mean bias for N's less than 30. In this study, simulations with small (20 and 30) and large (50 and 100) N's found that mean bias adjustments for larger N's are seldom needed. However, z transformations improved confidence intervals even for N = 100. The improvement was not in the estimated standard errors so much as in the asymmetrical CI's estimates based upon the z transformation. The resulting observed probabilities were generally accurate to within 1 point in the first non-zero digit. These issues are an order of magnitude less important for accuracy than design issues influencing the accuracy of the results, such as reliability, restriction of range, and N. DOI:10.2458/azu_jmmss_v1i2_gorsuch","PeriodicalId":90602,"journal":{"name":"Journal of methods and measurement in the social sciences","volume":"1 1","pages":"52-65"},"PeriodicalIF":0.0,"publicationDate":"2011-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"69054636","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This study focused on the quality of life experienced by persons with severe mental illness (SMI). Previous studies indicate the need for a multi-dimensional approach to the study of quality of life and its subjective indicators. For the SMI, attention should be paid not only to the direct and intentional effects of interventions, but also to the indirect and unintentional effects, both negative and positive. Hence, a global evaluation of individuals within this group is indicated. A multitrait-multimethod approach to construct validation using confirmatory factor analysis was employed. The hypothesized factors were modeled as multiple traits and the multiple perspectives of the respondents (i.e. patient, case manager, family member) were multiple methods. A total of 265 severely mentally ill adults served by a network of agencies in four cities were randomly sampled. The sample was approximately 50% male and 50% female, ages ranged from 19-78 years. DOI:10.2458/azu_jmmss_v1i2_johnson
{"title":"Construct validation of quality of life for the severely mentally ill","authors":"G. W. Johnson","doi":"10.2458/V1I2.101","DOIUrl":"https://doi.org/10.2458/V1I2.101","url":null,"abstract":"This study focused on the quality of life experienced by persons with severe mental illness (SMI). Previous studies indicate the need for a multi-dimensional approach to the study of quality of life and its subjective indicators. For the SMI, attention should be paid not only to the direct and intentional effects of interventions, but also to the indirect and unintentional effects, both negative and positive. Hence, a global evaluation of individuals within this group is indicated. A multitrait-multimethod approach to construct validation using confirmatory factor analysis was employed. The hypothesized factors were modeled as multiple traits and the multiple perspectives of the respondents (i.e. patient, case manager, family member) were multiple methods. A total of 265 severely mentally ill adults served by a network of agencies in four cities were randomly sampled. The sample was approximately 50% male and 50% female, ages ranged from 19-78 years. DOI:10.2458/azu_jmmss_v1i2_johnson","PeriodicalId":90602,"journal":{"name":"Journal of methods and measurement in the social sciences","volume":"1 1","pages":"31-51"},"PeriodicalIF":0.0,"publicationDate":"2011-05-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"69060652","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Patrick E. McKnight, M. Johns, P. McGovern, Julius Najab
Our present social sciences are at risk of losing sight of their primary purpose: the goal of reducing uncertainty. For years social scientists have drifted slowly toward the routine of employing of accepted methodological, conceptual, and analytical tools rather than engaging in problem oriented inquiry. Scientific contributions are reviewed in accordance to their compliance with the routine application of tools rather than focusing on their ability to problem-solve for a wider population. Researchers in every area of psychology for instance now insist on using methods such as random assignment and control groups, as well as data analytic procedures such as null hypothesis significance testing without regard to their relevance. A problem-focused inquiry would not dictate the routine use of any particular tool but rather the judicious application of tools when deemed appropriate. The following article describes the current situation in the framework contrasting toolbased and problem-focused inquiry and offers several insights that may create a more balanced and fruitful approach to scientific inquiry. DOI:10.2458/azu_jmmss_v1i2_mcknight
{"title":"The Pitfalls of a Tool-based Science and the Promise of a Problem-focused Science","authors":"Patrick E. McKnight, M. Johns, P. McGovern, Julius Najab","doi":"10.2458/V1I2.99","DOIUrl":"https://doi.org/10.2458/V1I2.99","url":null,"abstract":"Our present social sciences are at risk of losing sight of their primary purpose: the goal of reducing uncertainty. For years social scientists have drifted slowly toward the routine of employing of accepted methodological, conceptual, and analytical tools rather than engaging in problem oriented inquiry. Scientific contributions are reviewed in accordance to their compliance with the routine application of tools rather than focusing on their ability to problem-solve for a wider population. Researchers in every area of psychology for instance now insist on using methods such as random assignment and control groups, as well as data analytic procedures such as null hypothesis significance testing without regard to their relevance. A problem-focused inquiry would not dictate the routine use of any particular tool but rather the judicious application of tools when deemed appropriate. The following article describes the current situation in the framework contrasting toolbased and problem-focused inquiry and offers several insights that may create a more balanced and fruitful approach to scientific inquiry. DOI:10.2458/azu_jmmss_v1i2_mcknight","PeriodicalId":90602,"journal":{"name":"Journal of methods and measurement in the social sciences","volume":"1 1","pages":"1-14"},"PeriodicalIF":0.0,"publicationDate":"2011-05-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"69060709","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
S. Sidani, R. Bootzin, P. Moritz, Dana Epstein, Joyal Miranda, J. Cousins
Participants’ preferences for treatment may deter enrollment in a randomized clinical trial (RCT). The Partially randomized clinical trial (PRCT) is proposed as an alternative design to increase enrollment rate and enhance representativeness of the sample. There is limited evidence supporting the advantages of the PRCT. This study aimed to examine enrollment and refusal rates, reasons for refusal, and clinical profile of persons who declined participation and those who enrolled, in the context of a RCT and a PRCT. Persons with chronic insomnia completed a questionnaire to determine if they met the eligibility criteria regarding type, frequency, and duration of insomnia. Those who declined participation indicated reasons for refusal. Enrollment rate was computed as the percentage of individuals who took part in the study out of those found eligible. Independent sample t-test was used to compare enrollees and non-enrollees on characteristics of insomnia. The results showed a higher enrollment rate in the RCT than PRCT. Reasons for refusal were similar under the RCT and PRCT. Significant differences between enrollees and non-enrollees were found on fewer characteristics in the RCT than PRCT. The results do not support the advantages of the PRCT in enhancing enrollment of participants in studies evaluating the effectiveness of behavioral treatments of chronic insomnia.
{"title":"Patterns of enrollment in randomized and preference trials of behavioral treatments for insomnia","authors":"S. Sidani, R. Bootzin, P. Moritz, Dana Epstein, Joyal Miranda, J. Cousins","doi":"10.2458/V1I2.100","DOIUrl":"https://doi.org/10.2458/V1I2.100","url":null,"abstract":"Participants’ preferences for treatment may deter enrollment in a randomized clinical trial (RCT). The Partially randomized clinical trial (PRCT) is proposed as an alternative design to increase enrollment rate and enhance representativeness of the sample. There is limited evidence supporting the advantages of the PRCT. This study aimed to examine enrollment and refusal rates, reasons for refusal, and clinical profile of persons who declined participation and those who enrolled, in the context of a RCT and a PRCT. Persons with chronic insomnia completed a questionnaire to determine if they met the eligibility criteria regarding type, frequency, and duration of insomnia. Those who declined participation indicated reasons for refusal. Enrollment rate was computed as the percentage of individuals who took part in the study out of those found eligible. Independent sample t-test was used to compare enrollees and non-enrollees on characteristics of insomnia. The results showed a higher enrollment rate in the RCT than PRCT. Reasons for refusal were similar under the RCT and PRCT. Significant differences between enrollees and non-enrollees were found on fewer characteristics in the RCT than PRCT. The results do not support the advantages of the PRCT in enhancing enrollment of participants in studies evaluating the effectiveness of behavioral treatments of chronic insomnia.","PeriodicalId":90602,"journal":{"name":"Journal of methods and measurement in the social sciences","volume":"1 1","pages":"15-30"},"PeriodicalIF":0.0,"publicationDate":"2011-05-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"69060242","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Multidimensional Scaling (MDS) has been used as a growth mixture modeling technique in psychological and education research in recent years. This note focuses on a detailed explanation of interpreting the scale values in MDS growth analysis. Since scale values from MDS growth analysis are based on the Euclidean metric, we attempt to offer some guidance on interpretation of the scale values in terms of percentage of change in growth between each time interval. This approach is illustrated with a hypothetical example, and it can be used in actual research settings. DOI:10.2458/azu_jmmss_v2i2_ding
{"title":"A Note on the Interpretation of Scale Values in Multidimensional Scaling Growth Analysis","authors":"Cody Ding","doi":"10.2458/V2I2.15988","DOIUrl":"https://doi.org/10.2458/V2I2.15988","url":null,"abstract":"Multidimensional Scaling (MDS) has been used as a growth mixture modeling technique in psychological and education research in recent years. This note focuses on a detailed explanation of interpreting the scale values in MDS growth analysis. Since scale values from MDS growth analysis are based on the Euclidean metric, we attempt to offer some guidance on interpretation of the scale values in terms of percentage of change in growth between each time interval. This approach is illustrated with a hypothetical example, and it can be used in actual research settings. DOI:10.2458/azu_jmmss_v2i2_ding","PeriodicalId":90602,"journal":{"name":"Journal of methods and measurement in the social sciences","volume":"2 1","pages":"102-106"},"PeriodicalIF":0.0,"publicationDate":"2011-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.2458/V2I2.15988","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"69066395","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Measuring individuals or groups longitudinally is frequently necessary in social science research and applications. Substantial research and discussion has focused on the statistical properties of measures of change and some of the psychometric problems involved This monte-carlo simulation study focused on properties of the measurement instruments used for obtaining scores that represent change or growth over five time points and examined how well scores from conventional tests and computerized adaptive tests used to measure individual growth curves reflect true change. Data representing four different patterns of individual change and a baseline no-change condition were generated from an item response theory (IRT) model. Different tests simulated were conventional peaked tests with narrow and wider difficulties and three levels of discrimination, and computerized adaptive tests (CATs) drawn from banks with the same levels of discrimination. Conventional tests were scored by number correct and IRT weighted maximum likelihood. Results showed that as the examinees’ scores moved from the difficulty levels at which the tests were concentrated, number-correct scores over-estimated true change and had increasing amounts of error. High discrimination conventional tests had the poorest recovery of change for both groups and individuals. IRT scoring of the conventional tests improved recovery of change somewhat. By contrast, CATs consistently estimated growth with minimum and consistent error and performed best with highly discriminating items. DOI:10.2458/azu_jmmss_v2i2_weiss
{"title":"Measuring Individual Growth With Conventional and Adaptive Tests","authors":"D. Weiss, Shannon Von Minden","doi":"10.2458/V2I2.15990","DOIUrl":"https://doi.org/10.2458/V2I2.15990","url":null,"abstract":"Measuring individuals or groups longitudinally is frequently necessary in social science research and applications. Substantial research and discussion has focused on the statistical properties of measures of change and some of the psychometric problems involved This monte-carlo simulation study focused on properties of the measurement instruments used for obtaining scores that represent change or growth over five time points and examined how well scores from conventional tests and computerized adaptive tests used to measure individual growth curves reflect true change. Data representing four different patterns of individual change and a baseline no-change condition were generated from an item response theory (IRT) model. Different tests simulated were conventional peaked tests with narrow and wider difficulties and three levels of discrimination, and computerized adaptive tests (CATs) drawn from banks with the same levels of discrimination. Conventional tests were scored by number correct and IRT weighted maximum likelihood. Results showed that as the examinees’ scores moved from the difficulty levels at which the tests were concentrated, number-correct scores over-estimated true change and had increasing amounts of error. High discrimination conventional tests had the poorest recovery of change for both groups and individuals. IRT scoring of the conventional tests improved recovery of change somewhat. By contrast, CATs consistently estimated growth with minimum and consistent error and performed best with highly discriminating items. DOI:10.2458/azu_jmmss_v2i2_weiss","PeriodicalId":90602,"journal":{"name":"Journal of methods and measurement in the social sciences","volume":"2 1","pages":"80-101"},"PeriodicalIF":0.0,"publicationDate":"2011-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"69065983","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
R.S. Rodger fully developed, more than three decades ago, probably the most powerful methodology which exists for detecting real differences among population means (μ’s) following an analysis of variance. Since it is a post hoc method, a theoretically infinite number of potential statistical decisions may be considered, but Rodger’s method limits the final number of decisions to a single set which contains exactly J-1 (i.e., v1, the number of means in a study minus one) of them. It also constrains the number of these J-1 decisions that may be declared statistically “significant.” Rodger’s method utilizes a decision-based error rate, and ensures that the expected rate of rejecting null contrasts that should not have been rejected (i.e., the type 1 error rate) will be less than or equal to either five or one percent, regardless of the number of contrasts examined by a researcher prior to finally deciding upon the scientifically optimal set of decisions. The greatest virtue of Rodger's method, though, is not its considerable power, but its explicit specification of the magnitude of the differences that the researcher will claim to exist among the population parameters. The implied true means that this method calculates are the theoretical population μ’s that are logically implied, and mathematically entailed, by the J-1 statistical decisions that the researcher has made. These implied true means can assist other researchers in confirming or disconfirming population parameter claims made by those who use Rodger’s method. A free computer program (SPS) that instantiates Rodger’s method, and thereby makes its use accessible to every researcher who has access to a Windows-based computer, is available from the author. DOI:10.2458/azu_jmmss_v2i2_roberts
{"title":"Simple, Powerful Statistics: An Instantiation of a Better ‘Mousetrap’","authors":"Mark D. Roberts","doi":"10.2458/V2I2.15989","DOIUrl":"https://doi.org/10.2458/V2I2.15989","url":null,"abstract":"R.S. Rodger fully developed, more than three decades ago, probably the most powerful methodology which exists for detecting real differences among population means (μ’s) following an analysis of variance. Since it is a post hoc method, a theoretically infinite number of potential statistical decisions may be considered, but Rodger’s method limits the final number of decisions to a single set which contains exactly J-1 (i.e., v1, the number of means in a study minus one) of them. It also constrains the number of these J-1 decisions that may be declared statistically “significant.” Rodger’s method utilizes a decision-based error rate, and ensures that the expected rate of rejecting null contrasts that should not have been rejected (i.e., the type 1 error rate) will be less than or equal to either five or one percent, regardless of the number of contrasts examined by a researcher prior to finally deciding upon the scientifically optimal set of decisions. The greatest virtue of Rodger's method, though, is not its considerable power, but its explicit specification of the magnitude of the differences that the researcher will claim to exist among the population parameters. The implied true means that this method calculates are the theoretical population μ’s that are logically implied, and mathematically entailed, by the J-1 statistical decisions that the researcher has made. These implied true means can assist other researchers in confirming or disconfirming population parameter claims made by those who use Rodger’s method. A free computer program (SPS) that instantiates Rodger’s method, and thereby makes its use accessible to every researcher who has access to a Windows-based computer, is available from the author. DOI:10.2458/azu_jmmss_v2i2_roberts","PeriodicalId":90602,"journal":{"name":"Journal of methods and measurement in the social sciences","volume":"34 1","pages":"63-79"},"PeriodicalIF":0.0,"publicationDate":"2011-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"69066460","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A. Figueredo, S. Olderbak, Vanya Alessandra Moreno
A social relations model was developed for 5 years of behavioral recordings from a captive colony of Zebrafinches (Taeniopygia guttata). A quantitative ethogram was applied, using one-zero focal animal sampling on an ethologically comprehensive checklist of 52 behavioral items (Figueredo, Petrinovich, & Ross, 1992). Of the 9 ethological factors previously identified, only 4 of the 6 social factors (Social Proximity, Social Contact, Social Submission, and Social Aggression) were used. Major results were as follows: (1) Individual finches showed systematically different response dispositions that were stable over a 5-year period as both subjects and objects of behavior; (2) Interactions between finches differed systematically by the sexes of both the subjects and the objects of behavior; (3) Behavioral interactions between finches and their mates differed systematically according to the subjects' sex, but also differed systematically from those with other members of the objects' sex; (4) Behavioral interactions between finches and their relatives differed systematically between different discrete categories of relatives, but did not vary as a systematic function of either graded genetic relatedness or familiarity due to common rearing; and (5) Behavioral interactions between finches and their relatives showed an overall bias towards preferential interactions with male relatives. DOI:10.2458/azu_jmmss_v1i1_figueredo
{"title":"A Social Relations Model for the Colonial Behavior of the Zebra Finch","authors":"A. Figueredo, S. Olderbak, Vanya Alessandra Moreno","doi":"10.2458/V1I1.77","DOIUrl":"https://doi.org/10.2458/V1I1.77","url":null,"abstract":"A social relations model was developed for 5 years of behavioral recordings from a captive colony of Zebrafinches (Taeniopygia guttata). A quantitative ethogram was applied, using one-zero focal animal sampling on an ethologically comprehensive checklist of 52 behavioral items (Figueredo, Petrinovich, & Ross, 1992). Of the 9 ethological factors previously identified, only 4 of the 6 social factors (Social Proximity, Social Contact, Social Submission, and Social Aggression) were used. Major results were as follows: (1) Individual finches showed systematically different response dispositions that were stable over a 5-year period as both subjects and objects of behavior; (2) Interactions between finches differed systematically by the sexes of both the subjects and the objects of behavior; (3) Behavioral interactions between finches and their mates differed systematically according to the subjects' sex, but also differed systematically from those with other members of the objects' sex; (4) Behavioral interactions between finches and their relatives differed systematically between different discrete categories of relatives, but did not vary as a systematic function of either graded genetic relatedness or familiarity due to common rearing; and (5) Behavioral interactions between finches and their relatives showed an overall bias towards preferential interactions with male relatives. DOI:10.2458/azu_jmmss_v1i1_figueredo","PeriodicalId":90602,"journal":{"name":"Journal of methods and measurement in the social sciences","volume":"1 1","pages":"19-34"},"PeriodicalIF":0.0,"publicationDate":"2010-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"69060197","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Animal behaviorists have made extensive use of GPS technology since 1991. In contrast, psychological research has made little use of the technology, even though the technology is relatively inexpensive, familiar, and widespread. Hence, its potential for pure and applied psychological research remains untapped. We describe three methods psychologists could apply to individual differences research, clinical research, or spatial use research. In the context of individual differences research, GPS technology permits us to test hypotheses predicting specific relations among patterns of spatial use and individual differences variables. In a clinical context, GPS technology provides outcome measures that may relate to the outcome of interventions designed to treat psychological disorders that, for example, may leave a person homebound (e.g. Agoraphobia, PTSD, TBI). Finally, GPS technology provides natural measures of spatial use. We, for example, used GPS technology to quantify traffic flow and exhibit use at the Arizona Sonora Desert Museum. Interested parties could easily extend this methodology some aspects of urban planning or business usage.
{"title":"GPS Technology and Human Psychological Research: A Methodological Proposal","authors":"P. S. A. Wolf, W. J. Jacobs","doi":"10.2458/V1I1.74","DOIUrl":"https://doi.org/10.2458/V1I1.74","url":null,"abstract":"Animal behaviorists have made extensive use of GPS technology since 1991. In contrast, psychological research has made little use of the technology, even though the technology is relatively inexpensive, familiar, and widespread. Hence, its potential for pure and applied psychological research remains untapped. We describe three methods psychologists could apply to individual differences research, clinical research, or spatial use research. In the context of individual differences research, GPS technology permits us to test hypotheses predicting specific relations among patterns of spatial use and individual differences variables. In a clinical context, GPS technology provides outcome measures that may relate to the outcome of interventions designed to treat psychological disorders that, for example, may leave a person homebound (e.g. Agoraphobia, PTSD, TBI). Finally, GPS technology provides natural measures of spatial use. We, for example, used GPS technology to quantify traffic flow and exhibit use at the Arizona Sonora Desert Museum. Interested parties could easily extend this methodology some aspects of urban planning or business usage.","PeriodicalId":90602,"journal":{"name":"Journal of methods and measurement in the social sciences","volume":"1 1","pages":"1-7"},"PeriodicalIF":0.0,"publicationDate":"2010-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.2458/V1I1.74","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"69060186","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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