## Linear vs. Logistic Probability Models: Which is Better, and When?

Interpretability Let’s start by comparing the two models explicitly. If the outcome Y is a dichotomy with values 1 and 0, define p = E(Y|X), which is just the probability that Y is 1, given some value of the regressors X. Then the linear and logistic probability models are: p = a0 + a1X1 + a2X2 + … + akXk    (linear) ln[p/(1-p)] = b0 + b1X1 + b2X2 + … + bkXk       (logistic) […]

## The Difference Between the Bernoulli and Binomial Distributions

You might already be familiar with the binomial distribution. It describes the scenario where the result of an observation is binary—it can be one of two outcomes. You might label the outcomes as “success” and “failure” (or not!). Or, if you want to get mathematical about it, you might label them “1” and “0.” You […]

## Logistic Regression Analysis: Understanding Odds and Probability

Probability and odds measure the same thing: the likelihood or propensity or possibility of a specific outcome. People use the terms odds and probability interchangeably in casual usage, but that is unfortunate. It just creates confusion because they are not equivalent. How Odds and Probability Differ They measure the same thing on different scales. Imagine how confusing it would be […]

## How to Conduct Probit and Logit Models (Binary Outcome Models)

Probit and Logit Models (Binary Outcome Models) ‍   Do you want to understand the factors that influence binary outcomes? Then you’ve come to the right place. In this article, we’ll delve into the world of Probit and Logit models, which are commonly used in statistical analysis to predict binary outcomes. Whether you’re a researcher, […]

## Logistic Regression Analysis: Understanding Odds and Probability

Probability and odds measure the same thing: the likelihood or propensity or possibility of a specific outcome. People use the terms odds and probability interchangeably in casual usage, but that is unfortunate. It just creates confusion because they are not equivalent. How Odds and Probability Differ They measure the same thing on different scales. Imagine how confusing it would be […]

## The Difference between Logistic and Probit Regression

Both are types of generalized linear models. This means they have this form: Both can be used for modeling the relationship between one or more numerical or categorical predictor variables and a categorical outcome. Both have versions for binary, ordinal, or multinomial categorical outcomes. And each of these requires specific coding of the outcome. For example, in both logistic and […]

## Importance of ethical considerations in a research

Ethical considerations form a major element in research. The researcher needs to adhere to promote the aims of the research imparting authentic knowledge, truth and prevention of error. Furthermore, following ethics enables scholars to deal collaborative approach towards their study with the assistance of their peers, mentors and other contributors to the study. This requires values […]

## Understanding the application of Structural Equation Modeling (SEM)

Data is present everywhere in the digital world today. It has become complex to manage vast amounts of data. Today, there exists almost 100 zettabytes of digital data in the world. If used well, this data can produce valuable insights which can help companies and governments to predict future trends. Consequently, many statistical models have […]

## Limitations and weakness of qualitative research methods

In order to gain in-depth knowledge of underlying reasons and motivations, qualitative research is conducted. However, qualitative research also has limitations. In my previous article, I discussed the limitations of the quantitative research approach.  In this paper, I would be discussing the limitations with respect to qualitative research. Time-consuming process  The major drawback associated with qualitative cultural […]

## Examples of threats to the internal and external validity of a research

Threats to internal validity Timeline: Time is of paramount importance in research. The opinions of respondents depend on the recall time to gather opinions. For example, if the researcher asks the respondents about satisfaction with products at a coffee store and where they will consume it. Then the validity of their answers will increase. However, in case […]

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