Intelligence led policing: how the use of crime intelligence analysis translates in to the decision-making


International Journal of Security and Terrorism •



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International Journal of Security and Terrorism • Volume: 4 (1)

(OLR) model. This model is “estimated by a method called Maximum Likelihood Estimation 

(MLE)” (Aldrich & Nelson, 1984: 49) that deals with “picking parameter estimates that imply 

the highest probability or likelihood of having obtained the observed sample Y” (p. 51; see 

also Agresti, 2002). 

An ordered response model can be developed as a linear probability model with the 

use of a continuous latent

5

 variable (Long & Freese, 2006). One assumption of the ordered 



response model is that an unmeasured (latent) variable, y

*

, that ranges from  – ∞  to + ∞ 



exists, and is “mapped to an observed variable y” (Long, 1997: 116), where the mapping 

from the latent variable is done with the response categories of not utilized, utilized some, 

and highly utilized in the current study. This division of y* into three “values of the observed 

y” (Long, 1997: 117) is done by thresholds, or cut points, that are denoted as 

τ

. Here a 



linear equation model is created by using log odds, where standardized coefficients are used 

the same way that the coefficients are used in a linear regression model (LRM). 

Another way of interpreting the results of ordinal-level outcomes is to use a non-

linear model—specifically, odds ratios—rather than standardized coefficients. In that regard, 

one  assumption  of  the  ordinal  regression  model  is  the  “parallel  regression  assumption 

[italics original] and, for the ordinal logit [logistic regression] model, the proportional odds 

assumption” [italics original] (Long & Freese, 2006: 197) where the intercepts may change, 

but the coefficients for the independent variables are unchanged for each equation (see also 

Powers & Xie, 1999). When “the assumption of parallel regressions is rejected, alternative 

models  should  be  considered  that  do  not  impose  the  constraint  of  parallel  regressions” 

(Long, 1997: 145). All of the three models in this study (i.e., command, patrol, and detective 

models) were tested with the likelihood-ratio test, particularly with a model

6

command in 



Stata (Long & Freese, 2006; Wolfe & Gould, 1998). It is “an omnibus test that the coefficients 

for all variables are simultaneously equal” (Long & Freese, 2006: 199), and it evaluates 

“how the log likelihood of the ORM would change if the constraint…was removed” (Long, 

1997:  143).  The  test  results  also  showed  that  all  three  models  in  the  current  study  are 

appropriate for the data.

3.2. Findings

3.2.1.Descriptive Statistics

The  descriptive  statistics  of  all  variables  (i.e.,  dependent,  explanatory  independent,  and 

control) used in the models are presented in the Table 2.



5

 

In this section, the “latent” concept does not represent the same thing as it represented in the factor 

analysis section. 

6

 

This is not an official Stata command.


31

Intelligence - Led Policing:

How the Use Of Crime Intelligence Analysis Translates in to the Decision-Making 

Table 2. Descriptive Statistics for Dependent, Explanatory Independent, and Control Variables

3.2.2. Multivariate Analysis

As indicated in the previous sections, the results from nonlinear models are not easy to 

interpret.  The  ordered  logit  is  mostly  “interpreted  in  terms  of  odds  ratios  for  cumulative 

probabilities” (Long, 1997: 138). In the current study, the results of ordered logit models are 

presented in terms of the percent change in odds. In other words, the percent change of the 

metric values in the odds of “higher versus lower outcomes” (Long & Freese, 2006: 218) in 

the dependent variable will be provided in this section. 

Variable

N

Measure 



Min.

Max.


Mean

SD

Dependent 



Command-level use CAa efforts

519


Ordinal

0

2



1.28

0.621


0 = not utilized

1 = utilized some

2 = highly utilized

Detectives use CAa efforts

521

Ordinal


0

2

1.25



0.627

0 = not utilized

1 = utilized some

2 = highly utilized

Patrol officers use CAa efforts

518


Ordinal

0

2



1.05

0.607


0 = not utilized

1 = utilized some

2 = highly utilized

Explanatory

Factor 1:  Statistical analysis

423


Continuous

-2.02


3.94

0

1



Factor 2:  Crime analysis

423


Continuous

-2.29


3.3

0

1



Factor 3:  Intelligence analysis

423


Continuous

-2.21


3.64

0

1



Factor 4:  Survey analysis

423


Continuous

-1.94


4.21

0

1



Factor 5:  Patrol strategy analysis

423


Continuous

-2.56


3.12

0

1



Factor 6:  Displacement analysis

423


Continuous

-3.06


3.74

0

1



Control

Crime analysis unit 

517

Dummy


0

1

0.65



0.479

(yes = 1, no = 0)

Unions in the agency

535


Dummy

0

1



0.61

0.489


(yes = 1, no = 0)

Agency size 

493

Continuous



0.09

6.32


1.637

0.983


(# of sworn x 1,000 

⁄ population)

Total operating budget 

535


Continuous

4,554


1,492,567

153,366


112,401

(dollars in 12-month period)

Organizational hierarchy b 

535


Continuous

0.19


4.65

1.33


0.627

[(min - max salary) 

⁄ min salary]

Crime rates 

500

Continuous



0

421.47


61.27

39.17


(# of crimes x 1,000 

⁄ population)

a

CA = crime analysis.



 

b

Unit in dollars.




: dosyalar -> makale
makale -> Araştırma Makalesi Research Article
makale -> Elektronik Sosyal Bilimler Dergisi
makale -> 1 Mukaddime, Sayı 1, 2010
makale -> Xülasə Bu məqalədə dini kult və kult qrupunun yaranma səbəbləri haqqında klassik və müasir
makale -> Iğdır Üniversitesi / Iğdır University Sosyal Bilimler Dergisi / Journal of Social Sciences
makale -> 23 GÜvenlik kavraminin realiZM, neorealizm ve kopenhag okulu çERÇevesinde tartişilmasi dr. Övgü kalkan küÇÜksolak
makale -> Bir düşünme biçimi olarak nihilizm, hiçbir değer tanımayan görüşlerin ortak
makale -> Araştırma Makalesi/Çeviri Research Article/Translation
makale -> Xv ve XVI yüzyılların önemli kaynaklarından olan tahrir defterleri tımar sistemin
makale -> R. Arabacı & C. Çankaya / Eğitim Fakültesi Dergisi XX (1), 2007, 1-15


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