Homeless female veterans population mental health and housing needs

Homeless female veterans population mental health and housin" rel="nofollow">ing needs 1. 700 word with in" rel="nofollow">intro describin" rel="nofollow">ing general differences between Quantitative and qualitative research. Describe the characteristics of a descriptive, exoerunebtak, quasi-experimental, correlational and multiple regression designs References needed).  Usin" rel="nofollow">ingin" rel="nofollow">ing homeless females are area of in" rel="nofollow">interest add a sentence or two to the followin" rel="nofollow">ing: 1. General topic area 2. Specific Topic 3. General problem (is mental health or trauma a cause) 4. SPecific Problem 5 Purpose of the study- examin" rel="nofollow">ine the cause of in" rel="nofollow">increase homelessness of female veterans. 6. Research Question that can be addressed in" rel="nofollow">in the mock study Summary. Listed below is my recommended 7-step process to construct an operational model: 1. Identify all your variables (in" rel="nofollow">independent variables, dependent variables, moderatin" rel="nofollow">ing or mediatin" rel="nofollow">ing variables, etc.). 2. Identify the data source of each variable (e.g. where is the data comin" rel="nofollow">ing from?). 3. Identify the type of date / level of measurement (e.g. nomin" rel="nofollow">inal, ordin" rel="nofollow">inal, in" rel="nofollow">interval, ratio). 4. Construct a figure that shows how the variables will operate for the test (this is your operational model, which is an illustration of theories synthesized for how the selected variables are expected to perform---remember, you must have scholarly peer-reviewed literature to support why each variable belongs in" rel="nofollow">in your operational model.  It is recommended to sketch it out on paper first and then, once it makes sense, transfer to PowerPoin" rel="nofollow">int to format and revise as needed - see PowerPoin" rel="nofollow">int example. 5. Include arrows/lin" rel="nofollow">ines to represent each hypothesis and label accordin" rel="nofollow">ingly (e.g. H1, H2, etc.). Position the arrows/lin" rel="nofollow">ines to show the logical flow of variable relationship. 6. Review the illustration to ensure it has logical operation / flow (e.g. it must align with the research questions and hypothesis and have a theoretical basis. 7. Post your operational model in" rel="nofollow">in PowerPoin" rel="nofollow">int in" rel="nofollow">in this learnin" rel="nofollow">ing thread and I will provide you with early feedback.   Please also in" rel="nofollow">include your research questions and hypothesis statements to clarify the data-analysis in" rel="nofollow">intent and overall alignment. Here is an example from the literature that may help: Migliore, L.A. and Chin" rel="nofollow">inta, R. (2016). Mobile technology and the Employee-Customer-Profit Chain" rel="nofollow">in. SAM Advanced Management Journal, Win" rel="nofollow">inter 2016, 81(1). http://search.ebscohost.com.contentproxy.phoenix.edu/login" rel="nofollow">in.aspx?direct=true&amp;db=bth&amp;AN=114643265&amp;site=ehost-live The research questions and hypotheses are shown on Pages 54-56, along with an illustration of the operational model and explanations of hypotheses development, research methodology, and data collection of sample.  The Migliore &amp; Chin" rel="nofollow">inta (2016) example may help in" rel="nofollow">increase your understandin" rel="nofollow">ing of the process to align research design, measurement, and analysis. A 1300 word (this section) The quantitative design that best addresses the RQ/s (experimental, quasi-experimental, predictive multivariate analysis (multiple regression, or other). [Simple descriptive or correlational research are not appropriate for this class, and generally not sufficient for a dissertation]: 8. The variables that will be measured in" rel="nofollow">in the design. Identify and operationally defin" rel="nofollow">ine your variables: Independent variables (IVs) [Three required]; and Dependent variable/s (DV/s). (Keep in" rel="nofollow">in min" rel="nofollow">ind your IVs are that which you "manipulate" and the DV is that which you measure.) Identify how you will measure each variable and defin" rel="nofollow">ine what kin" rel="nofollow">ind of measurement this represents - nomin" rel="nofollow">inal, ordin" rel="nofollow">inal, in" rel="nofollow">interval, or ratio (Discrete [Categorical]; Contin" rel="nofollow">inuous). Ensure that your type of data "fits" with your choice of analysis, by reviewin" rel="nofollow">ing the assumptions required to meet a particular analysis in" rel="nofollow">in SPSS®. 9. The in" rel="nofollow">inferential statistical technique that will best serve to examin" rel="nofollow">ine your variables. Usually, experimental and quasi-experimental designs use ANOVAs (MANOVA, ANCOVA); and correlational designs with multiple variables use multiple regression. Ensure when you discuss your analysis you use the appropriate language that is, usin" rel="nofollow">ing "effect" with measurin" rel="nofollow">ing differences of means (groups) for an ANOVA; and usin" rel="nofollow">ing "relationship" and/or "prediction" with correlational designs. 10.The Hypotheses (Hyps). Include a null (H0- no significant fin" rel="nofollow">indin" rel="nofollow">ings); and an alternative (H1- significant fin" rel="nofollow">indin" rel="nofollow">ings) hypothesis to represent each variable that will be in" rel="nofollow">included in" rel="nofollow">in your analysis. 2; 3. 1800 word paper that in" rel="nofollow">introduces the population, samplin" rel="nofollow">ing and in" rel="nofollow">instrumentation for a mock study. It must in" rel="nofollow">include an identified population and the method that can be used to select a sample (numbered as 11). 12&gt; Identify a chosen in" rel="nofollow">instrumentation for the variables (an edistin" rel="nofollow">ing quantatitive assessment in" rel="nofollow">instrument such as MLQ, LPI or NCLEX-RN) Write a 1,750- to 2,400-word paper that in" rel="nofollow">introduces the population, samplin" rel="nofollow">ing, and in" rel="nofollow">instrumentation for your mock study. Indent and in" rel="nofollow">include an updated outlin" rel="nofollow">ine identifyin" rel="nofollow">ing the population, samplin" rel="nofollow">ing approach, sample size, its adequacy (statistical power), for your mock study; provide clear and concise in" rel="nofollow">information that: 11. Identifies your population, and in" rel="nofollow">includes the method you will use to select your sample. 12. Identifies your chosen in" rel="nofollow">instrumentation for your variables, that is, select an existin" rel="nofollow">ing quantitative assessment in" rel="nofollow">instrument/s, for example, the MLQ, LPI, Burnout Inventory, state assessment exam, or NCLEX-RN exam that would be appropriate to the topic and the population. Ensure that your outlin" rel="nofollow">ine is aligned. Include additional paragraph/s discussin" rel="nofollow">ing how you would collect data from your participants. Summarize your paper with a conclusion at the end of your Microsoft® Word document in" rel="nofollow">includin" rel="nofollow">ing justification for your choices supported by references. A conclusion javascript:; Pages 141-157 in" rel="nofollow">in Ch. 5 of Christensen, Johnson, and Turner (2014) Christensen, L., Johnson, R., &amp; Turner, L. (2014).  Introduction to scientific research.  Research Methods, Design and Analysis.  Pearson Education, Inc</p>