Dissertation Proposal Statistics involving causal modelling

As a part of the dissertation proposal, a scholar has to state the exact manner in which he plans to use his data, define the relationship between variables and arrive at the result of analysis. When you learn about the interrelations of the variables, you will be able to construct a chain of variables, called causal models that lead to some behavioural outcome. This technique is the subject of an increasing number of research publications and academicians are devoting attention to the development of causal models. So, it would be an added advantage if you can adopt such a technique in your proposal.

The background research is crucial to convincing readers of a proposal that a basis for the model exists. Assemble the prior research that undergirds each of the parts of the model and supply the rationale to piece together the literature. The literature review will naturally lead into a description of the proposed model in conceptual terms. The conceptual definition of a variable is often at variance with its operationalisation. So, you will have to describe the operationalisation in the original research as well as in your planned study. Readers can then judge the analysis in relation with the original. In order to portray a variable in all its conceptualized aspects, it is common to represent it with more than one operationalisation. Indicate in the proposal where you have done this, and describe the advantage this lends to your study, when compared to previous studies. When doing Dissertation Proposal Statistics using this method, you can check the efficacy of your technique by assessing whether you have provided strong descriptions for the following:

• Research problem and study rationale
• Relationship to be examined, treatment effectiveness to be assessed, or prediction to be confirmed
• Population and samples to be studied
• Treatment, conceptual definition, operational definition and fidelity of implementation
• Methods of data collection, including development and quality of instrumentation
• Procedures for assessing changes and eliminating or controlling alternative explanations
• Methods of data analysis, including quality control procedures
• Ethical concerns and accommodations
• Study timeline, resources and management issues

Taking Statistics Help for completing this stage will help you answer all these questions positively. Since this is a continuously evolving field, unless you have appropriate training in the field, you may want to consult a PhD statistician to ensure that what you plan is currently sound. Moreover, the plan needs to be described in sufficient detail, to ensure that the members of the committee will have little trouble in following it. When you offer enough material for discussion, you will be able to take a rationale point of view from the committee.

 

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