Evaluating and comparing profiles of burglaries developed using three statistical classification techniques: cluster analysis, multidimensional scaling, and latent class analysis
While there are a variety of statistical classification techniques available, the most prominent in the behavioral sciences are Cluster Analysis (CA), Multidimensional Scaling (MDS), and Latent Class Analysis (LCA). Researchers often rely on person-oriented statistical classification techniques to i...
1. VerfasserIn: | |
---|---|
Beteiligte: | |
Medienart: | Elektronisch Aufsatz |
Sprache: | Englisch |
Veröffentlicht: |
2022
|
In: |
Psychology, crime & law
Jahr: 2022, Band: 28, Heft: 1, Seiten: 34-58 |
Online-Zugang: |
Volltext (lizenzpflichtig) |
Journals Online & Print: | |
Verfügbarkeit prüfen: | HBZ Gateway |
Schlagwörter: |
MARC
LEADER | 00000caa a22000002 4500 | ||
---|---|---|---|
001 | 1783529512 | ||
003 | DE-627 | ||
005 | 20211224235908.0 | ||
007 | cr uuu---uuuuu | ||
008 | 211223s2022 xx |||||o 00| ||eng c | ||
024 | 7 | |a 10.1080/1068316X.2021.1880582 |2 doi | |
035 | |a (DE-627)1783529512 | ||
035 | |a (DE-599)KXP1783529512 | ||
040 | |a DE-627 |b ger |c DE-627 |e rda | ||
041 | |a eng | ||
084 | |a 2,1 |2 ssgn | ||
100 | 1 | |a Fox, Bryanna |e VerfasserIn |0 (DE-588)1208512145 |0 (DE-627)1694814645 |4 aut | |
109 | |a Fox, Bryanna |a Fox, Bryanna Hahn |a Hahn, Bryanna Fox |a Fox, Bryanna H. | ||
245 | 1 | 0 | |a Evaluating and comparing profiles of burglaries developed using three statistical classification techniques: cluster analysis, multidimensional scaling, and latent class analysis |
264 | 1 | |c 2022 | |
336 | |a Text |b txt |2 rdacontent | ||
337 | |a Computermedien |b c |2 rdamedia | ||
338 | |a Online-Ressource |b cr |2 rdacarrier | ||
520 | |a While there are a variety of statistical classification techniques available, the most prominent in the behavioral sciences are Cluster Analysis (CA), Multidimensional Scaling (MDS), and Latent Class Analysis (LCA). Researchers often rely on person-oriented statistical classification techniques to identify and understand the latent heterogeneity in the complex individuals that we study. Using data on 405 randomly selected solved burglaries committed in Florida, this study is the first to conduct a head-to-head comparison of the benefits and weakness of each analysis and evaluate the resultant typologies and predictive validity when all three analyses are applied to the same dataset. Findings suggest that the number and nature of resultant subtypes differ depending on the statistical classification technique employed. We conclude that LCA is superior to MDS and CA due to its ability to objectively evaluate model fit and handle missing data, balance of parsimony and complexity in the results, and reliability and accuracy stemming from the first test of predictive validity among the three statistical classification techniques. Implications for future research and the application and testing of statistical classification techniques are also discussed. | ||
650 | 4 | |a Typologies | |
650 | 4 | |a multidimensional scaling | |
650 | 4 | |a Latent Class Analysis | |
650 | 4 | |a Cluster Analysis | |
650 | 4 | |a classification techniques | |
650 | 4 | |a Burglary | |
700 | 1 | |a Escue, Melanie |e VerfasserIn |4 aut | |
773 | 0 | 8 | |i Enthalten in |t Psychology, crime & law |d Getzville, NY : HeinOnline, 1994 |g 28(2022), 1, Seite 34-58 |h Online-Ressource |w (DE-627)341903574 |w (DE-600)2070124-X |w (DE-576)27234995X |x 1477-2744 |7 nnns |
773 | 1 | 8 | |g volume:28 |g year:2022 |g number:1 |g pages:34-58 |
856 | 4 | 0 | |u https://doi.org/10.1080/1068316X.2021.1880582 |x Resolving-System |z lizenzpflichtig |3 Volltext |
935 | |a mkri | ||
951 | |a AR | ||
ELC | |a 1 | ||
LOK | |0 000 xxxxxcx a22 zn 4500 | ||
LOK | |0 001 4026371573 | ||
LOK | |0 003 DE-627 | ||
LOK | |0 004 1783529512 | ||
LOK | |0 005 20211223061534 | ||
LOK | |0 008 211223||||||||||||||||ger||||||| | ||
LOK | |0 035 |a (DE-2619)KrimDok#2021-12-22#3910094A1A92927E72FBCCD9E853C65E0BEA95DA | ||
LOK | |0 040 |a DE-2619 |c DE-627 |d DE-2619 | ||
LOK | |0 092 |o n | ||
LOK | |0 852 |a DE-2619 | ||
LOK | |0 852 1 |9 00 | ||
LOK | |0 935 |a zota | ||
ORI | |a SA-MARC-krimdoka001.raw |