So, can you imagine easily passing your degree with the grades you want?

If your dissertation or thesis research question resembles this, then the analysis you may want to use is a logistic regression.

Logistic regression is a statistic that allows group membership to be predicted from predictor variables, regardless of whether the predictor variables are continuous, discrete, or a combination of both.

In the example above, the group to which we are trying to predict membership is "librarians". The predictor variables are age, marital status, glasses, and favorite color.

Why would research want to predict such group membership? In the health sciences, research frequently examines whether or not a subject will get a disease based on a number of predictors. For example, your question may ask if age, weight, gender, tobacco use, and marital status predict whether a subject gets cancer.

When to Use Logistic Regression Logistic regression is the statistic to use when your dependent variable is anticipated to be nonlinear with one or more of your independent variables. For example, the probability of one of the Model dissertation research proposal getting cancer may not be affected too much by a 5-cigarettes-smoked difference among subjects who are light smokers say per daybut may change a lot with an equal difference among subjects who are heavy smokers say a day.

In this example, we must ask whether the predictor variables can predict the constant cancer. The most direct way to do this is to compare a model with the constant plus the predictor variables to a model with just the constant. If the analysis, the logistic regression, indicates a reliable difference between the two models, then there is a significant relationship between the predictors and the outcome cancer.

Using the above example, we would compare the model which consists of the prediction variables age, weight, gender, tobacco use, and marital status and the constant cancer to a model which consists of only the constant cancer.

If the model with the predictors is significantly different than the model with just the constant alone, then our model with the predictors can be said to predict the outcome cancer better than no predictors at all.

You may be thinking that, of course, having predictors is better than not having any predictors at all! But what if your predictor variables were things like favorite color, type of car owned, presence of braces, and pet ownership?

Would these predictor variables predict the constant cancer reliably? Another way to see if the predictor variables predict the outcome cancer is to compare a model with only some of the predictor variables plus the constant with a model with all of the predictor variables plus the constant, called the "full model".

Continuing our example, we might compare the model of the predictor variables age and weight plus the constant cancer to a model with all of the predictor variables age, weight, gender, tobacco use, and marital status plus the constant cancer. The objective here is to find the best model "fit".

That is, you want your model to do the best job of predicting the constant cancer with the fewest predictor variables.

Types of Logistic Regression There are several types of logistic regression that can be used for dissertation and thesis analyses.

They include direct, sequential, and stepwise logistic regressions. Which one you use for your analysis depends on your research.

In analysis using direct logistic regression, all of the predictor variables are entered into the equation at the same time.The conclusion chapter can either make or break the grade of your research/dissertation paper.

So you should take your time when it comes to choosing the design. The methods section describes actions to be taken to investigate a research problem and the rationale for the application of specific procedures or techniques used to identify, select, process, and analyze information applied to understanding the problem, thereby, allowing the reader to critically evaluate a study’s overall validity and reliability.

Doctoral Student Dissertation Title Area/Methodology Graduate Program; Arts and Humanities: Shannon Baley: Towards a Gestic Feminist Dramaturgy: Close Reading, Description, Performative Writing, Performance Ethnography. The elaboration likelihood model (ELM) of persuasion is a dual process theory describing the change of attitudes.

The ELM was developed by Richard E. Petty and John Cacioppo in The model aims to explain different ways of processing stimuli, why they are used, and their outcomes on attitude change. Study. Experiencing Ratings Orientation Population Outcome Measures and Findings; Kirtner & Cartwright Manner of Process rated for first therapy hour.

This Research Proposal was prepared by Mr Takkiddin, a Master of Islamic banking student at INSANIAH University College. He sores A+ for this excellence work.

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Guidelines on writing a research proposal