Sampling Design Report: Transitional Housing

Sampling Design Report: Transitional Housing

The paper will discuss the sampling design used in two studies of transitional housing. The strengths and limitations of sampling designs used in each study will be identified. Also, an alternative sampling design for each review will be determined. The sampling designs of the following case studies will be discussed. “They give you back that dignity”: understanding the intangible resources that make a transitional house a home for homeless familiar and A place to rest: the role of transitional housing in ending homelessness for women in Calgary, Canada.

The first research by Fleary, Joseph, Zhang, & Quirion (2019) used a non-probability sampling method in which convenient sampling was done. The case study was about a transitional housing program, and semi-structured interviews of past and current residents of a transitional housing program were carried out. The purposive sampling was used by the authors to collect data because it aligned with the study. The interview was done to people who used to live or were living in a transitional home. It was a deliberate selection by the researcher of the population to recruit for data collection.

The strengths of the sampling method utilized in the study were its efficiency and convenience (Wolf, Joye, Smith, & Fu, 2016). Since the participant were beneficiaries of the program or in the process of undergoing the program, it was very convenient for the researcher to carry out the study. Another strength of using a non-probability sampling method in the study was that it was impossible to collect a probability sampling since the survey was only carried out in one transitional housing program.

The limitations of using non- probability sampling in this study was that the researchers were unable to know how well the population of homeless people undergoing transitional housing program was represented (Sharma, 2017). By studying only one transitional housing program, the research lacked the inclusiveness of the population of the study. Another limitation is that the researchers could not calculate the margin of errors in their case study. Also, they were at risk of encountering bias in their finding.

An alternative sampling design that would be appropriate for the case study is clustered sampling, which is a probability sampling method. Instead of collecting information from one transitional housing program, the researchers could have selected several programs in the region of study and then randomly select the participants for the interviews. Using this method would have changed the outcomes of the study by giving a representation of the whole region rather than apart. The number of people interviewed would have increased, causing the elimination of bias. Also, the researcher would gather more information on transitioning and give more diverse recommendations.

In Fotheringham, Walsh, & Burrowes (2014) case study, they used a non-probability sampling method to collect data. The researchers used quota sampling, where they chose nine women to participate in a ten weeks’ reflection process. The nine women proportionally represented the women who had experienced homelessness and were in permanent settlements after going through the transitioning process. The researchers specified the quota of subjects to be involved in the process.

The strengths of using quota sampling design are its convenience and cost because it is non-probability sampling. Another advantage is its straightforwardness and representation potential (Sharma, 2017). By using a selected number of people in the population that have their experiences specific to the subject of study allowed the data to be straightforward in its findings. Also, their responses are a potential representation of the whole population.

By using quota sampling, various limitations can be encountered. The first limitation is the inability to find the sampling error. Another challenge would be sampling bias because the researcher may choose to overlook certain significant features for the affluence of access (Lamm & Lamm, 2019). Also, quota sampling understates issues that do not fall in the groups selected.

An alternative design of sampling, such as random sampling would have been effective in the study.  By using a probability sampling design instead of a non-probability, one would have augmented the result in different ways, such as the findings in the challenges of transitioning from homelessness to permanent housing. Using random sampling could have provided a larger number of a participant in the reflection process causing more diversity in the finding which could have otherwise been lacking due to the few participants. When the number of participants is large, there is a limited possibility for bias because of the diversity in the experiences of participants.

The two research studies used non- probability sampling designs for their studies, which was convenient since they were subject particular in making decisions. The non-probability method through convenient and cost effective it has limitations such as bias and lack of inclusiveness in its findings. However, every sampling design has its strengths and limitation. Therefore one should use the design that is well suited with the study and population to achieve inclusive and unbiased information from the samples used.