Looking for a PhD level person who can read a journal article and respond to a set of questions I have. Good research methodology and statistics is required. Job should take no more than five pages. Again, it is a stratight forward respond to question and not an eassay type job. Here are the questions.
Use the questions as headings thereby breaking up the review responses into sections.
Problem: What is the managerial (practical) problem and main academic (theoretical) purpose behind (underlying) this article? Is the managerial problem important (yes or no)? What is the managerial importance of the article? What is the academic importance of the article? Defend your positions on all of these issues.
Consider Contribution: As indicated by the questions that follow, technical correctness and theoretical coherence are obvious criteria in evaluating an article, but don't forget to consider the overall contribution that the manuscript offers. Is the contribution or the article meaningful, interesting, or important? Defend your position.
Make a case in favor of why you think and/or the authors think that studying the problem is important). In discussing its importance, please consider both its practical and theoretical significances.
Looking at the Theory, is there an untested assumption worth testing?
Central Hypothesis: State the central hypothesis or main proposition expressed/explored? Is your (the central) hypothesis best classified as descriptive, explanatory, or predictive/causal? Does the main hypothesis call for a measure of association or a measure of difference between two or more variables? Defend your position on these issues. What is the theoretical basis of your (the central) hypothesis? Does this hypothesis
(1) logically flow from and relate to the theorized constructs and relationships presented as the basis for the research or
(2) was it picked out of thin air?
What is the quality of the references cited? Are those references scholarly and/or relevant to the subject? Show the relationship being described by your (the central) hypothesis (for example, the reliance on advertising revenue causes online media businesses to fail) as a function in which the dependent (effect or criterion) variable(s) is(are) a function of the independent (cause or predictor) variable(s). Sometimes an article shows how causes are interrelated or effects are interrelated. If this is the case in the article you are reviewing, show A to be a function of B and B to be a function of A.
Looking at the Hypotheses, is there a variable that was omitted that might explain why the author did not obtain expected results?
Please limit your statement of your (the central) hypothesis, in which should show the dependent (criterion) variable(s) or Y as a function of the independent (predictor) variable(s) or X, to one sentence. What information do the authors of the article present in support of your chosen hypothesis? Please pick and choose among all the points that the authors make and list only those points that are relevant to your chosen hypothesis.
Research Design: What is the research design? Is it an Experimental Design? Is it a Quasi-Experimental Design? Is it a Correlational Design? Comment on the appropriateness of the design.
Please limit the statement of the research design to one sentence.
Construct Validity/Reliability: Restate your (the central) hypothesis, look for a description of how the cause (that is, the independent (or predictor variable(s)) and the effect (that is, the dependent (or criterion variable(s)) are being measured. For every variable in your central hypothesis comment on:
Face Validity: Do the measures measure what they are supposed to measure?
Internal reliability: Are the measures reliable?
Level of Measurement: What level of measurement is applied to these variables (for example, for each, identify if they are nominal, ordinal, scalar).
Unit of Analysis: What is the unit of analysis (for example, is it individual, group, corporate, societal)? Does the unit of analysis match between variables?
In your (the central) hypothesis, look for a description of how the cause (that is, the independent (or predictor variable(s)) and the effect (that is, the dependent (or criterion variable(s)) are being measured. That is, what is (are) the dependent variable(s) in the central hypothesis? How was (or were) the dependent variable(s) in the central hypothesis measured? How well is (are) the dependent variable(s) operationalized (e.g. unacceptable, acceptable, or superior - or - poor, average, or outstanding)? Defend your position. What is (are) the independent variable(s) in your hypothesis? How was (or were) the independent variable(s) in your hypothesis measured? How well is (are) the independent variable(s) operationalized (e.g. unacceptable, acceptable, or superior - or - poor, average, or outstanding)? Defend your position.
Looking at the Variables, would operationalizing the dependent or independent variables in other ways have yielded other results?
External Validity: Was a sample drawn? If so, how was it drawn? Was it a large, randomly drawn sample? Was one or more samples drawn from a single population or were samples drawn from different populations? Or, was sampling not done, at all?
Was the sampling procedure unacceptable, acceptable, or superior - or - poor, average, or outstanding? Defend your position, and offer suggestions for how the sampling procedure(s) might have been improved (if improvement is needed). Having no sample does not make the conclusion(s) in the article wrong but justification should be given for not sampling. Can the sample be generalized to other samples, settings, or populations? (e.g., If students were asked to rate the taste of soft drinks, does that apply (or not apply) to other consumers?) Defend your position on these issues.
Looking at the Sample, would different results have been obtained if another sample had been used?
Internal Validity: Relating back to your discussion of the research design, how was the data collected? Was the data collection procedure unacceptable, acceptable, or superior - or - poor, average, or outstanding? Defend your position and offer suggestions for how data collection procedure(s) might be improved (if improvement is needed).
Examine the setting in which the data was collected: Observation, Review of documents, Survey, Experiment, or Personal interview. Does the data collection process make sense? Were data collected to test the author’s central hypothesis? Defend your positions on these issues
Conclusion Validity (Or Statistical Conclusion Validity)? Identify the descriptive statistics used in the study. Did the descriptive statistics measure differences or relationships? Was there any statistical or qualitative analysis to test your (the central) hypothesis? Identify the analytic statistics used in the study. Did the analytic statistics test for the significance of the differences or relationships? Were the analytic statistics approriate? If not, what analytic statistics do you propose the authors should have used? Were the statistical methods used in the study appropriate for the level of measurement of the data? Defend your positions on these issues.
Implications: What are the implications of the research reported in the article for future research? If reported, do you agree with these implications? If not reported, how can the research reported in the article be extended? Defend your position on these issues.
Looking at the Implications and suggestions for future research, is there something listed that you might like to tackle?
Improve: How would you improve any other aspects of the paper that you haven’t discussed above?
Be Specific: Identify problems not discussed elsewhere and explain how these problems can be addressed (where possible). These comments should be in the form of specific comments, reactions, and suggestions. The more specific you can be, the better. It is also helpful if you organize your statements by numbering your points or paragraphs
Identify Strengths: While it is important to identify critical weaknesses, it is equally important to identify major strengths. Distinguish between limitations not discussed elsewhere that can be fixed in a follow-up study and those that definitely cannot.