Category: BLOG

In quality of life data, it is common to have the outcome measures as ordinal e.g., points on a Likert Scale. These outcome measures are based on attributes that cannot be assessed directly, such as pain or satisfaction level. One of the major difficulties that we come across while analyzing the ordinal outcome measures is that these data preclude any arithmetic operations, such as addition or subtraction etc. When it comes to measurement of change in ordinal outcome measures for longitudinal data, one either uses standard classical methods such as the paired t-test, repeated measures or the effect size statistics to test the statistical significance of the change. However, these approaches have some critical issues. Let’s discuss about scores as outcome measures which are ordinal in nature. Being ordinal, the…

P values are ubiquitous in medical literature and are often misinterpreted. The p value is often misunderstood as probability that the null hypothesis is true. But it should be noted that the null hypothesis is not random. It can be either true or not. In fact, a p-value is the probability under a specified null hypothesis that a statistical summary of the data would be equal to or more extreme than its observed value. For example, when we detect the difference in means of total bilirubin levels measured in two samples, we would like to know how likely it is to get such or more extreme difference when there is no actual difference between underlying populations. This is what p value tells us, and using the observed data if we…

Occam's (or Ockham's) razor is an idea attributed to William of Ockham, a 14th century logician. The idea suggests that explanatory entities should not be multiplied beyond necessity. In statistical context, when you have two competing models that fit the data equally well, Occam’s razor recommends to ‘shave away all but what is necessary’. The concept of parsimony is based on Occam’s razor, which also proposes that the model with fewer parameters to be preferred to the one with more. Principle of Occam’s razor finds one of its applications in regression analysis. In regression analysis, one of the most important issues is which predictor variables to include in the model. One common question arises: ‘Are these many predictor variables needed in the model or a model with fewer number of…