Week 11 project

Guns

Age, Citizen, Races

The model represents and displays a process in which lower-income families' attitudes on firearms change over time. Guns determine or have an impact on people's ages, citizenship, and race. Furthermore, age, citizenship, and color are all influenced by lower-class income. In the graph above, the Guns variables serve as mediators.

Results and Discussion

We need to get the correlation coefficients of these three relationships to see if these three conditions are met. In Appendix 01, the Pearson Product-Moment correlation coefficient will be calculated, and the two-tailed significance test will be presented. Each path's correlation coefficient, or the link between variables, is statistically significant. Lower-income people report a very strong association between their factors and other variables. These findings show that, at the bivariate level, all of the necessary conditions for the test mediator's likely role have been met.

The original regression coefficient and standard error of this regression coefficient for the association between the IV and the intermediary and the association between the intermediary and the DV were then calculated using two simple linear regressions (adjusted for IV). Appendices 02 and 03 can be used to obtain the regression coefficient and standard error of the correlation between IV and the intermediate. Gun is the dependent variable in the first regression model, with all other factors acting as independent variables.

The findings reveal that the age coefficient has a negative impact on firearms. The number of guns drops as people get older, although this does not affect the model. Citizenship has a beneficial effect on guns but does not affect the model. Furthermore, Races has a beneficial effect on Guns, with a minimal effect on the model. Furthermore, the value of the constant in the second model has a substantial impact on the model. Furthermore, the value of weapons has a detrimental influence on low-income people, because those with higher wealth will buy fewer firearms for security reasons, and the number of persons buying weapons for security purposes will decrease by 1%. Citizen and Guns are unaffected by any of the other variables in this model.

The key purpose is to use these two regressions to assess the analysis's intermediate impacts. We use the Sobel test to accomplish this (see Appendix 05). The Sobel test statistics are 0.34, 0.54, and 0.46, with related p-values, indicating IV and DV (in this example, guns, and age) and associated p-values, that is, the observed p-value is not lower than the specified alpha 0.05 level, suggesting IV and DV (in this case, guns and age). Because of intermediates (weapons), the relationship between citizens and ethnicity in low-income homes is not included in the model; in other words, there is no evidence of mediation.

References

Carlson, J. (2013). Clinging to their guns? The new politics of gun carry in everyday life (Doctoral dissertation, UC Berkeley).

Levine, P., & McKnight, R. (2020). Three Million More Guns: The Spring 2020 Spike in Firearm Sales. Washington, DC: Brookings Institution.

http://quantpsy.org/sobel/sobel.htm

Appendix

Appendix 01

Appendix 02

Appendix 03

Simple Linear Regression Model 1

Appendix 04

Simple Linear regression Model 2

Appendix 05

Sobel Test (For Age and Having Gun)

Sobel Test (For Citizen and Having Gun)

Sobel Test (For Races and Having Gun)