Posted: March 24th, 2023

Quantitative Methods and Designs

Part 1: Non-Experimental Research

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A Brief Description of the Purpose of the Study

Researchers should have a clear objective and direction when conducting a study. Silverman (2016) suggests that the purpose of a study gives a direction that the entire process will take considering what the researcher seeks to accomplish. Hogan (2014) provided a clear goal for his research, “Socioeconomic Factors Affecting Infant Sleep-Related Deaths in St. Louis.” Therefore, at the end of the article, the reader can evaluate whether the purpose was met using the particular research design selected by the researcher.

The study emanates from previous evidence on racial disparity in infant sleep-related deaths, especially between African Americans and Caucasians. Hence, it was critical for Hogan (2014) to determine the possibility of modifiable factors that might play a role in reducing racial disparity in the problem. The purpose of the study was to establish whether a relationship exists between the mother’s socioeconomic factors and infant sleep-related deaths. The factors studied include the mother’s “level of poverty, race, level of education, and number of children born” (Hogan, 2014, p. 11). The author sought to establish possible interventions if he found a relationship between the variables by modifying the socioeconomic factors to change the mother’s situation and the ability to provide better care to their infants.

The Specific Research Question

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The article has a clear research question that the researcher answered by collecting data. Notably, even non-experimental studies are guided by a research question that a scholar(s) uses to collect relevant quantitative data (Silverman, 2016). Hogan (2014) includes a section in the article labeled research question for the reader to locate the genesis and direction of the stud. The research question for the non-experimental study is to find out whether a relationship exists between “(level of poverty, race, level of education, and number of children born), pertaining to the mother and infant sleep-related deaths” (Hogan, 2014, p. 11). Therefore, the data collected for the study emanates from this research question.

The Population and Sample

Researchers identify a population and perform sampling from which to collect data. Sampling is critical due to the vastness of the study population. Therefore, it is crucial to obtain a sample of manageable units that is representative of the whole population (Silverman, 2016). Regardless of the nature of the quantitative study, sampling is a necessary process. Although Hogan (2014) performed a non-experimental study, the article contains precise information on the nature of the sample used to collect data. The author collected secondary data from a dataset between January 1, 2005 and December 31, 2009. The dataset provided information on 26,211 individuals and represented all births recorded in the setting of the study, St. Louis, MO. Sampling, in this case, was necessary to narrow down the period of study to get manageable cases.

Besides, Hogan (2014) reveals the type of sampling that was used in the study. The author acknowledges the use of a systematic sampling of all mothers in St. Louis when the infant was born and resided in the same place past their first birthday. Furthermore, the researcher used information from Medicaid and food stamp program’s enrollment to get information about “Infant Death” as it was critical in the study. Hogan (2014) provides sufficient information on the sample and the sampling method used to get the number of units to provide important data to answer the research question reliably. The population from which the sample was obtained is also clearly stated. Therefore, the reader can understand the process used to obtain numerical data for the non-experimental study.

The Methods Section

The methods section shows the actual implementation of the research. The process indicates the way data was collected to answer the research question, including the design, recruitment, participant descriptions, measurement instruments, and details about data collection and analysis. All the information should be specified explicitly in the methods section of the article. Given that the researcher was performing a quantitative study, the choice between experimental, non-experimental, and quasi-experimental was necessary. Hogan (2014) used a non-experimental research design to collect quantitative data. Polit and Beck (2017) define non-experimental research as the process when the researcher does not engage in the manipulation of the independent variables. Such a study does not include random assignment of participants to experimental and control conditions (Bleske-Rechek, Morrison, & Heidtke, 2015). Non-experimental studies do not involve evidence of changes in independent variables causing differences in the dependent variables since they do not include any manipulation.

Since Hogan (2014) did not engage in the manipulation of any variable to answer the research question, a nonexperimental design was suitable for the study. The article further reveals the nature of the data collection method used in the study. Hogan (2014) used observational approaches, comparing outcomes in cases where death occurred to those where no death transpired using a case-control approach. Furthermore, since the researcher lacked control over the original data collection process as the study involved collection of secondary data, the study was an observational one.

Besides the research approach and data collection methods, the inquiry provides information about participants and the way the cases were obtained for inclusion in the study. The recruitment information was obtained from all births recorded at St. Louis, MO between January 1, 2005 and December 31, 2009. The researcher obtained permission to engage in the study from the Missouri DHSS institutional review board. Hogan (2014) reveals the use of two populations in the study for comparison purposes, “all mothers of infants younger than 1 year who resided in St. Louis, MO at the time of the infant’s birth and whose infants died in St. Louis between January 1, 2005 and December 31, 2009” (p.11). The researcher also used a control population of mothers who had lived in St. Louis when the infants were born and remained there beyond their first birthday.

A reliable study should include the measures used in the data collection and analysis process. Hogan (2014) used variables that affected parental choices for infant’s safe sleep as the measures in the study. The author further matched birth/death data with the International Statistical Classification of Diseases and Related Health Problems, Tenth Revision (ICD-10; WHO, 2006). The coding system for the different categories of deaths were also revealed, “Code R95 for SIDS, Code W75 for accidental suffocation or strangulation in bed-involving linens, caregiver’s body, or pillow/mattress, and Codes R96- 99 for death for which no cause could be discovered” (Hogan, 2014, p. 11). The data was collected for outcome variable (sleep-related death) and other demographic independent variables. From data collection, it is imperative for the researcher to show how the data was analyzed. Since the data collected was quantitative, the researcher would most definitely use a statistical data analysis method (Polit & Beck, 2017).  The analytical method used in the study was descriptive analysis, Chi-square, and logistic regression.

A Summary of the Findings

The analysis of the data collected by the researcher leads to results or findings that establish whether the research question was answered. From the statistical analysis, Hogan (2014) wanted to establish whether there was a relationship between “(level of poverty, race, level of education, and number of children born) pertaining to the mother and infant sleep-related deaths” (p. 11). Evidence from the study reveals that on controlling for birth records of infants, who lived beyond their first birthday, the analytical methods, Chi-square, and logistic regression, confirmed a relationship between race and poverty and infant sleep-related deaths. The other two demographic variables, level of education and number of children were not revealed to have considerable impact on infant sleep-related deaths.


Contrary to other previous studies that have shown strong relationships between socioeconomic variables and infant sleep-related deaths, the current study revealed a correlation between only race and poverty. However, Hogan (2014) suggested some areas for future study, including further investigation of the role played by maternal level of education in sleep-related infant deaths. Furthermore, the research has limitations that could be addressed in future studies, such as the size of the sample, accuracy of the birth and death records, precision in diagnosing the time of death, and the potential limitation in the generalizability of findings because of the primary focus on African American population. The information reveals the foundation for future research on the topic.

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