• Summarizing Statistical Results

• Summarizing Statistical Results
For this discussion, find two journal articles that take a quantitative approach to looking at a problem that relates to family dynamics.
In your initial post, cite the articles and explain the statistical quantitative technique used in each. For example, state whether the study used multiple regression, correlation, t-test, or another technique for analysis. Explain whether or not the results of each study were statistically significant; be sure to include the p-value, percentage of error. Provide a summary of each study’s purpose, method, and findings using language that a client with a 10th grade education could understand.
Your initial post must cite at least two references and be at least 250 words in length, not counting the reference list or a repetition of the discussion topic. Cite your sources in APA 6th edition format.
Response Guidelines
Respond to the initial posts of at least two other learners. When responding, evaluate the clarity of the other learners’ summaries:
• What areas are unclear?
• What information needs more elaboration?
• What suggestions for improvement would you offer?

Learner Post 1:
The issue that I chose to examine was families with children with disabilities. The first article found, written by Axelsson, Granlund, and Wilder (2013) focused on engagement in family activities for children with profound intellectual and multiple disabilities (PIMD) in comparison to children with typical development. This quantitative study analyzes the data collected from questionnaires by using Mann–Whitney U-test and Spearman’s rank correlation test.The overall results of this study found that children with typical development were more engaged in the activities that their families participated in. The p-value of this study was set to P < 0.05. Which makes the results very significant in this area in showing that there is a definite difference in the two groups of children. This information could be used to help parents to increase the involvement of children with PIMD.
The second article focused on the neurocognitive outcomes in children with four chronic illnesses. Moser, Veale, McAllister, and Archer (2013) research the measures in which the intellectual and cognitive characteristics.The data collected was taken from age appropriate achievement tests for each child. The study looked at many areas in combination with academic performance, educational status, educational measurement, learning, achievement, developmental delay, learning disabilities, intellectual disabilities, behavioral disorders, IQ, cognition, school problems, absenteeism, school attendance, anxiety, learning regression, or developmental regression. The p-value listed in this study was P < 0.01. Therefore, one would be able to consider the results found in this study to be very reliable for use and in determining how well students with the listed problems will be able to function in the classroom.

Axelsson, A. K., Granlund, M., & Wilder, J. (2013). Engagement in family activities: a quantitative, comparative study of children with profound intellectual and multiple disabilities and children with typical development. Child: Care, Health & Development; 39(4), 523-534. doi:10.1111/cch.12044.
Moser, J. J., Veale, P. M., McAllister, D. L., & Archer, D. P. (2013). A systematic review and quantitative analysis of neurocognitive outcomes in children with four chronic illnesses. Pediatric Anethesia, 23 (11), 1084-1096. doi:10.1111/pan.12255
Learner Post 2:
Articles and monographs studying families and children overwhelmingly report some type of statistical tests or measures, what are sometimes called quantitative analysis (Greenstein & Davis, 2013). Although the language of statistical analysis may seem a bit daunting at first, the good news is that you can develop a basic ability to interpret the results of common statistical techniques fairly easily (Greenstein & Davis, 2013). In these times of increasingly scarce resources, economic evaluation in family therapy research are important to the long-term viability of the field as a whole (Sprenkle & Piercy, 2005).

Rosano, A., Mancini, F., & Solipaca, A. (2009). Poverty in people with disabilities: Indicators from the capability approach. Social Indicators Research, 94(1), 75-82. doi:http://dx.doi.org/10.1007/s11205-008-9337-1

The methodology was based on the estimation of coefficients able to identify the number of additional income units necessary for a family with one or more disabled members to obtain the same level of economic satisfaction as a household with no disabled members. The methods reported in the literature derive from the relationship between responses on satisfaction with income and income level in the various conditions compared, such as number of household members and the presence/absence of disabilities. Various instruments have been developed, such as those used in diverse studies by Dubnoff et al. (1981), Vaughan (1984) and Poulin (1988), to estimate equivalence scales in the United States and Canada. Subjective wellbeing was measured by asking interviewees to evaluate their level of perceived satisfaction with their income, by choosing the most appropriate adjective from a list. The same method is also used in this study. Level of satisfaction with household income was recorded on a nominal 4-point scale (low, moderate, high, very high) and coded from 1 to 4. In order to analyze the correlation between income and satisfaction with economic condition, econometric techniques based on the ordered probit model were used, in line with the cited British study on poverty rates in households with disabled members (Kuklys 2005). Ordered probit is a statistical model that estimates the probability of a certain event as a function of a set of explanatory variables. In this model, the events considered are probability is estimated, is level of satisfaction with household income, taking account of the needs of all household members. The reference situation is a household of one person without disabilities. An adjusted model has also been calculated which takes account of the mental health of the interviewee, as evaluated with the SF-121 questionnaire (Ware et al. 1996), so that this can be taken into consideration in the subjective evaluation of satisfaction with income. In fact, people with a mental health problem may evaluate their resources negatively beyond all reasonable considerations.

Jarjoura, G. R., Triplett, R. A., & Brinker, G. P. (2002). Growing up poor: Examining the link between persistent childhood poverty and delinquency. Journal of Quantitative Criminology, 18(2), 159-187. doi:http://dx.doi.org/10.1023/A:1015206715838

Using longitudinal data spanning 14 years, measures of level of exposure to poverty and its timing are constructed and used to examine the poverty–delinquency relationship. In addition to considering the ways that poverty makes a difference in the propensity for delinquent involvement, these data also allow us to consider the ways that poverty shapes the lives of children to enhance their likelihood for delinquency. Results in the child development literature point to the impact of poverty on such outcomes as cognitive development, school achievement, and emotional well-being (Brooks-Gunn et al., 1997). These outcomes have been linked to delinquency in criminological research, and thus, are likely candidates for mediating the relationship between poverty and delinquency. Several measures of family context and peer interaction are also included in this analysis as factors which might mediate the relationship between poverty and delinquency. The age of the mother at the time of the youth’s birth is included, as is the birth order within the family for the youth. Dummy variables are included indicating whether the youth’s biological father is living in the home at the time of the 1990 interview, and whether the youth ever lived away from his or her mother while growing up. The quality of supervision by the mother is indicated by the mother’s report (from the 1992 interview) about how often she knows with whom the youth is when not at home. This is a four-category measure in which the responses include (from lowest to highest): all of the time, most of the time, some of the time, only rarely. To capture the influence of the youth’s peers, we include a measure of whether the youth reported pressure from peers to engage in negative behaviors. This variable is coded to indicate the number of different things the youths felt pressure from their friends to do from among the following list, as reported in the 1992 interview: try cigarettes; try marijuana or other drugs; drink beer, wine or liquor; skip school; or commit a crime, or do something violent. A ‘‘0’’ indicates no peer pressure to do any of these things. A ‘‘5’’ indicates peer pressure to do all of these things. Control variables are also included in the analysis: the youth’s age, gender and race. Gender is represented by a dummy variable coded 1 for females and 0 for males. Different dummy variables are included for each of two racial subgroups: black and Hispanic.


Greenstein, T. N., & Davis, S. N. (2013). Methods of family research. (3rd ed.). Thousand Oaks, CA: SAGE Publications, Inc.

Jarjoura, G. R., Triplett, R. A., & Brinker, G. P. (2002). Growing up poor: Examining the link between persistent childhood poverty and delinquency. Journal of Quantitative Criminology, 18(2), 159-187. doi:http://dx.doi.org/10.1023/A:1015206715838

Rosano, A., Mancini, F., & Solipaca, A. (2009). Poverty in people with disabilities: Indicators from the capability approach. Social Indicators Research, 94(1), 75-82. doi:http://dx.doi.org/10.1007/s11205-008-9337-1

Sprenkle, D. H., & Piercy, F. P. (Eds.). (2005). Research methods in family therapy. New York, NY:

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