CONTRASTE INDICACIONES Y PERCEPCIONES

To answer the research questions, these questions need to be tested in the form of hypotheses. The testing of these hypotheses is performed with the application SPSS. With the aid of the results of the investigation files and by means of cross-tabs, a chi-square test

and Cramer’s V test will be conducted in SPSS, in order to examine whether a statistically significant relation exists between the variables.

2.5.1 Chi-square test and Cramér’s V test

Crosstabs are used to examine the association between variables. The variables are derived from the case study results. The chi-square test7 _{(χ2-test) will determine whether a relation} exists between two variables in a crosstab. This test is based on a comparison of the observed values in the table with what one might expect if the two distributions would be completely independent. In other words, the probability will be assessed if the data in the table occurred by chance. The expected value is determined by the software as an estimate of the number of responses while assuming that there is no relation between the variables. The actual value is the entered data from the case study. If these two numbers are close together, there is no association between the variables; the value of one variable is not affected by the other. If the numbers are widely apart then there is obviously a relation between the variables. The higher the value, the stronger the relation between the variables. To determine whether the observed value deviates significantly from the expected value, it is compared to the critical chi-squared value. This value is dependent on the desired reliability of the test (which is similar to the Z-value of the sample) and the number of degrees of freedom. A value less than 0.05 means that there is a significant relation between the variables. A value higher than 0.05 indicates that there is no significant relation, and so that the hypothesis should be rejected. The chi-square test indicates whether or not it is worth to further examine all row and column percentages.

Because the chi-square test is not a clear measure for the association between two variables, this test is e.g. strongly influenced by the size of the sample, a corrected test will be used, namely Cramér's V. The calculation of Cramér's V is based on chi-square. The latter gives an indication of the strength of the association between two variables, but is not an association measure because there is no upper limit. The strength of this association will be calculated by using Cramér's V-test in SPSS. A Cramer's V score of 0.10 can be considered as a good threshold value for suggesting the presence of a significant relation between the two

variables. 8 _{However, the results of the chi-square test and Cramér's V only indicate whether} there is a connection, and how strong this connection is. These test cannot give further information on the direction of the connection. The test is limited to statements about whether the correlation between the two variables is based purely on chance, or that there is an actual relation between the two variables is present.

2.5.2 Logistic regression

Three dependent variables are identified in this study to identify: weapon use, victim resistance and victim injury. Given the dichotomous nature of these variables, it is a possibility to perform a logistic regression analysis. Logistic regression analysis is used to examine the impact of a variable on an event, after observing other important variables. In order to interpret the results of this analysis, both B and exp(B) are used. B is the regression coefficient, and it shows how much the logit changes while there is a single point change in the independent variable. Because this does not explain much, exp(B) is used, that indicates with what number the odds must be multiplied when the independent variable increases 1 point. The independent variables are encoded with the values 0 and 1. An odds ratio of 8,562 implies that if moved from one group to another, the independent variable is increasing with one, the odds of the occurrence of the dependent variable will increase with 8,562. When B is positive, exp(B) will be larger than 1. This means that the chance of belonging to the group of firearm users increases when the independent variable increases. When B is negative, exp(B) will be smaller than 1. This means that the chance of belonging to the group of firearm users decreases when the independent variable increases (Verhagen, 2007).

8 _{The coefficient ranges from 0 to 1 (perfect association). The following guidelines can be used for} interpreting Cramer’s V correlations. These are only crude estimates for interpreting strengths of correlations. If Cramer’s V = .01 to .05 (No or negligible relationship), .06 to .10 (weak relationship), .11 to .15 (Moderate relationship), .15 to .25 (Strong relationship), .25 or higher (Very strong relationship). Source: http://faculty.quinnipiac.edu/libarts/polsci/statistics.html