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Article 1:
Golinelli, D., Tucker, J. S., Ryan, G. W., & Wenzel, S. L. (2015). Strategies for obtaining probability samples of homeless youth. Field Methods, 27(2), 131-143. 

Abstract: Studies of homeless individuals typically sample subjects from few types of sites or regions within a metropolitan area. This article focuses on the biases that can result from such a practice. We obtained a probability sample of 419 homeless youth from 41 sites (shelters, drop-in centers, and streets) in four regions of Los Angeles County (LAC). We found that restricting the frame to only certain types of sites or geographic regions biased the sample in terms of demographic and background characteristics as well as rates of risky behaviors. For example, homeless youth who can be found in shelters (vs. those who do not use shelters) and Hollywood (vs. other regions of LAC) tend to be younger, minorities, and engage less in risky behaviors. Recommendations are provided for evaluating the tradeoffs between bias and cost in selecting a sampling strategy for studies of homeless individuals.

Questions that apply to this article:

1. What type of sampling is often used when sampling homeless youth?
2. Why did the researchers develop two site frames for gathering the sample?
3. The multistage design used in this study consisted of three stages: (1) selection of sites, (2) selection of site days within sites, and (3) selection of youth within site days. This led the researchers to a sample of youth visits rather than a sample of homeless youths. What was the reason for sampling in this manner?

Article 2:
Engel, R. S., & Calnon, J. M. (2004). Examining the influence of drivers' characteristics during traffic stops with police: Results from a national survey. Justice Quarterly, 21(1), 49-90.

Abstract: The political and social pressure for police departments to collect race-based traffic and pedestrian contact information has led to the accumulation of abundant sources of police-citizen contact data. Many of the current data collection efforts, however, do not include accurate benchmarks for data comparisons. The strengths and limitations of the six most prominent benchmark measures used in current studies of police citizen contacts—census data, observations of roadway usage, official accident data, assessments of traffic violating behavior, citizen surveys, and internal departmental comparisons—are described. Focusing on the Project on Police-Citizen Contacts, a large-scale data collection effort of traffic stops for the Pennsylvania State Police, four different benchmarks for statewide comparisons are described. The continued improvement of data collection efforts at the local and state levels through the use of multiple benchmark measures is discussed.

Questions that apply to this article:

1. Why must data collected by police officials be evaluated/critiqued?
2. What two concerns are involved with the reliability and validity of citizens’ race for data collected directly by police?
3. How can validity for data collected by police be increased?