Which of the following is a limitation of the National crime & victimization survey?

Description

The BJS National Crime Victimization Survey (NCVS) is the nation's primary source of information on criminal victimization. Each year, data are obtained from a nationally representative sample of about 240,000 persons in about 150,000 households. Persons are interviewed on the frequency, characteristics, and consequences of criminal victimization in the United States. The NCVS collects information on nonfatal personal crimes (i.e., rape or sexual assault, robbery, aggravated and simple assault, and personal larceny) and household property crimes (i.e., burglary/trespassing, motor vehicle theft, and other types of theft) both reported and not reported to the police. Survey respondents provide information about themselves (e.g., age, sex, race and Hispanic origin, marital status, education level, and income) and whether they experienced a victimization. For each victimization incident, the NCVS collects information about the offender (e.g., age, race and Hispanic origin, sex, and victim-offender relationship), characteristics of the crime (e.g., time and place of occurrence, use of weapons, nature of the injury, and economic consequences), whether the crime was reported to police, reasons the crime was or was not reported, and victim experiences with the criminal justice system.

Description

The National Crime Victimization Survey (NCVS) is the nation's primary source of information on criminal victimization. Each year, data are obtained from a nationally representative sample of about 240,000 persons in about 150,000 households. Persons are interviewed on the frequency, characteristics, and consequences of criminal victimization in the United States.

The NCVS collects information on nonfatal personal crimes (i.e., rape or sexual assault, robbery, aggravated and simple assault, and personal larceny) and household property crimes (i.e., burglary/trespassing, motor vehicle theft, and other types of theft) both reported and not reported to the police. Survey respondents provide information about themselves (e.g., age, sex, race and Hispanic origin, marital status, education level, and income) and whether they experienced a victimization.

For each victimization incident, the NCVS collects information about:

• the offender, including age, race and Hispanic origin, sex, and victim-offender relationship
• characteristics of the crime, including time and place of occurrence, if weapons were used, the nature of any injury sustained by a victim, and economic consequences to the victim related to their victimization
• whether the crime was reported to police
• reasons the crime was or was not reported
• and victim experiences with the criminal justice system.

The survey has been ongoing since 1973. For more information, see the NCVS data collection page. 

Can NCA predict the presence of the outcome?

Can NCA solve the problem of measurement error?

Can NCA handle outliers?

Can NCA prove causality?

Can NCA solve the problem of convenience sampling for statistical inference?

Can NCA predict the presence of the outcome?

No. NCA only can predict the absence of an outcome, not the presence of the outcome. NCA focuses on single conditions (and their combinations) that prevent the outcome to occur. Traditional sufficiency methods such as Multiple Regression, Structural Equation Modeling, Partial Least Squares, as well as methods like QCA consider the complete causal structure that produces the outcome. These methods must be used to predict the presence of the outcome from a set of conditions.

Can NCA solve the problem of measurement error?

No. Just like other data-analysis approaches NCA presumes that the data to be analysed are valid and reliable (and calibrated). If this assumption is not correct the results of the NCA analysis can be flawed. When NCA is used for describing the sample or for making point estimates of the population from which the sample is drawn, NCA is not sensitive for measurement error of observations (far) below the ceiling line, but sensitive for measurement error of observations around the ceiling line.

Can NCA handle outliers?

No/Yes. If the outlier is caused by measurement error, the results of an NCA may be flawed (see measurement error). If the outlier is a real phenomenon, NCA can handle this outlier: if the outlier is below the ceiling, NCA results are not affected; if the outlier is above the ceiling, NCA takes the outlier into account (the ceiling includes the outlier). Note that all cases around the ceiling are “best cases”: with relatively low input (X) they achieve a relatively high output (Y).

Can NCA prove causality?

No. Just like other data analysis techniques, NCA alone cannot prove causality. It depends largely on the research design and the available theory whether or not it is plausible that the condition is a necessary cause. Experimental designs are preferred for that purpose. Observational studies need solid theory to infer causality.

Can NCA solve the problem of convenience sampling for statistical inference?

No. Just like other data-analysis approaches NCA presumes that the sample is a probability sample (e.g., random sample) from the population. Although this requirement is seldom met, if this assumption is not true the results of the NCA analysis (and any other data analysis approach for statistical inference) can be flawed.

What are some of the limitations of the National crime victimization?

Which of the following is the limitation of the National Crime Victimization Survey quizlet?

Which of the following is a limitation of the National Crime Victimization Survey NCVS )?

Which of the following is an important limitation of the NCVS quizlet?