Running head: QUANTITATIVE RESEARCH METHOD 1 Problem Statement ****TURN THIS INTO A PROBLEM STATEMENT**** Divorce rate amongst men and women, who were reared in an absent father home. CONSIDER PROFESSORS COMMENTS REFERENCE MY ATTEMPT AT MY PROBLEM STATEMENT. “In this current form, it is not yet a problem statement. It does describe a potential topic for research problem to surface. But a research problem comes from a gap. And a gap is a lack of knowledge. A lack of explanation. It migjt be helpful if you posed your topic area within the context of IV-DV relationship or predictor – criterion relationship. A gap is a lack of explanation as to why the IV affects the DV. Or a lack of explanation as to what the IVs are that affect the DV. (This is typical in a quantitative research. We will discuss in another venue, the nature of a gap in qualitative research). So a gap is a lack of the middle variable—usually. A watered-down example would be that in the olden times people thought that Time (IV) caused the spoon to rust (DV). But what was in Time that led to the RUST? Now that’s the gap. A lack of explanation. It was when scientists posed Oxidation as the variable that immediately explained the rusting better that the gap was filled. The new variable, the middle variable was oxidation. That was the contribution to the literature.” Scholarly Resources Cherlin, A. J. (2005). American Marriage in the Early Twenty-First Century. Future Of Children, 15(2), 33-55. Gladdings, S. T., & Huber, C. H. (1984). The Position of the Single-Parent Father. Journal Of Employment Counseling, 21(1), 13. doi:10.1002/j.21611920.1984.tb00783.x Klaus, D., Nauck, B., & Steinbach, A. (2012). Relationships to stepfathers and biological fathers in adulthood: Complementary, substitutional, or neglected?. Advances In Life Course Research, 17(Special issue on Intergenerational Relations), 156-167. doi:10.1016/j.alcr.2012.01.006 Lauroba, E. e. (2014). The Effects of Divorce on Children. International Journal Of Legal Information, 42(1), 55-66. Running head: QUANTITATIVE RESEARCH METHOD 2 Mack, K. (2001). Childhood family disruptions and adult well-being: the differential effects of divorce and parental death. Death Studies, 25(5), 419-443. MAJA, P. (2017). The importance of the absence of the father in the narrations of Adult Children of Divorce. Wychowanie W Rodzinie , Vol III, Iss 3/2011, Pp 115-134 (2017), (3/2011), 115. doi:10.23734/wwr20113.115.134 Running head: QUANTITATIVE RESEARCH METHOD 3 The Quantitative Method Utilizing the Quantitative Method could provide numerical data that would be used to statistically analyze data in order to highlight the link if any between divorce, gender, age, and absent fathers. The Quantitative Method identifies the relationship between the four aforementioned variables. This would identify cause and effect; thus, could make a successful prediction. In this particular instance it would be best to use the experimental design since there is a need to establish a cause and effect relationship among men and women ages 18-40 (this will be broken down into two groups 18-28 and then 2938) that were reared without their biological father. Divorce would be the independent variable as there is hope that it would be manipulated based on a father’s presence. Purpose The purpose of this Quantitative Study is to identify the relationship between divorce and marital success in participants reared in an absent father home. **** FIX THESE TO BE CORRECT?****Research Questions 1. What is the relationship between gender and divorce amongst participants who were reared in an absent father home? 2. What is the relationship between gender, age, and geographical location and divorce? 3. How common is divorce amongst participants who were raised with both biological parents? Running head: QUANTITATIVE RESEARCH METHOD 4 Hypothesis Divorce is more common amongst men and women, ages 29-38 that were reared without their biological father in the home. Population and Sample To avoid bias it is best to use random sampling so that each participant is given the opportunity to participate. The population to be analyzed are men and women between the ages of 18-40 who live in the following cities in Alabama; Huntsville, Decatur, and Madison. Who were previously divorced or are divorced currently. Due to the population size, it would be in the best interest of the study to select individuals to participate who would be representatives sampling thus random selection procedures. This data is best analyzed by utilizing the nominal scale. This is because there is intent to place people and attributes into categories based on how they were reared, gender, and a specific age bracket. The next step is to identify the number of times in which divorce or martial success occurred. The desired end state requires the use of inferential statistics as well as the need to predict/ infer success or failure in the identified population. It is even more practical to use correlation over regression. Type I and Type II Errors (also known as alpha and beta errors) Type I is best defined as a false positive, rejecting a null hypothesis is correct (Derks, Zwinderman, & Gamazon, 2017). Type II is best defined as a failure to reject a false null hypothesis, a false negative (Derks, Zwinderman, & Gamazon, 2017). In the posed problem I believe a Type II would be more Running head: QUANTITATIVE RESEARCH METHOD 5 common in that the answer would be incredibly different depending on when it was conducted. For instance, if this study was done some ten years ago when singly parent homes were less prevalent it could alter the results and need for the study drastically. The best way to avoid type II errors is to depend heavily on estimation utilizing confidence intervals (Derks, Zwinderman, & Gamazon, 2017). The changes of a study detecting an effect where there is an effect to be detected is known as statistical power. Statistical power can be influenced in this proposed study by the sample size, experimental design, and variance. With random sampling and the age ranging from 18-40 it yield the higher statistical power. Running head: QUANTITATIVE RESEARCH METHOD 6 References Derks, E. M., Zwinderman, A. H., & Gamazon, E. R. (2017). The relation between inflation in type-I and type-II error rate and population divergence in genome-wide association analysis of multi-ethnic populations. Behavior Genetics, 47(3), 360-368. doi:10.1007/s10519-017-9837-3 Judd, C. M., Westfall, J., & Kenny, D. A. (2017). Experiments with more than one random factor: Designs, analytic models, and statistical power. Annual Review Of Psychology, 68601-625. doi:10.1146/annurev-psych-122414033702
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