[…]scale, discrete variables and continuous variables. Continuous variables can assume any value, for example blood pressure or blood glucose levels. Variables that can only take on certain values, such as integers, are labelled discrete variables. Examples of discrete variables are the number of children in a family, or the number […]
[…]a study protocol This web-page describes the differences between aim, objective, hypothesis and research questions. Reading this will help you choose these wisely when you write your own study protocol for your next research […]
[…]He concludes a single principle, the existence of thoughts. He says that he is a thinking being and formulated this in the famous phrase; I think, therefore I am. Descartes asks if there is anything else you can be sure of. He uses the example of a figure made of vax. […]
[…]data sets. Many statistical software packages delivers this if you tick the right box when you command the software to do logistic regression. Calibration slope. Reclassification: Reclassification table. Reclassification calibration. Net Reclassification Index (NRI) Integrated Discrimination Index (IDI) Clinical usefulness Net Benefit (NB) Decision curve analysis (DCA) The most commonly […]
[…]Propensity score matching (PSM) is a new technique allowing retrospective data to be used for group comparisons estimating effect of a treatment. PSM can be done in several different ways . It has been argued that PSM is slightly better than multivariate regression for the purpose of comparing effect between […]
[…]data is encoded / transformed into units of meaning. Units of meaning are arranged and combined to form one or more categories. Often, several categories are combined into one (or more) overall themes / essences / theories / main interpretations. Examples of this highest abstraction level are:— phenomenology – Essence— […]
[…]to a number between 10-50 or higher. However, a proper sample size calculation can only be done for research question VI above . There is no sensible way to make a proper sample size calculation for research question I-V. Effectiveness and efficacy Efficacy is a measure of effect of the […]
[…]should be linear. Testing if prerequisites (assumptions) are fulfilled The assumptions should be tested for in some way for each independent variable. The easiest way is to create a Kaplan-Meier curve for each independent variable and simply look at the graph. It will tell you if there is a reasonably […]
[…]which is then being tested. The hypothesis is a theoretical construction based on previous research and new ideas. The purpose of grounded theory is to do the opposite, that is, creating new theories purely based on observation of the reality you unconditionally explore. Hence, in grounded theory there is no […]
[…]describes level of significance and how this relates to p-values. These are sometimes mixed up and reading this page will enable you to understand the difference. The difference between level of significance (alpha) and the p-value A low p-value says it is unlikely that we would get the observed observations if the […]
