Category: Learning modules »

Interpreting multivariate analysis with more than one dependent variable

In continuation to my previous article, the results of multivariate analysis with more than one dependent variable has been discussed in this article. Read more »

Multivariate analysis with more than on one dependent variable

The normal linear regression analysis and the ANOVA test are only able to take one dependent variable at a time. So one cannot measure the true effect if there are multiple dependent variables. In such cases multivariate analysis can be used. Thus, multivariate analysis (MANOVA) is done when the researcher needs to analyze the impact on more than one dependent variable. Read more »

Non linear regression analysis in STATA and its interpretation

In the previous article on Linear Regression using STATA, a simple linear regression model was used to test the hypothesis. However the linear regression will not be effective if the relation between the dependent and independent variable is non linear. The non linear regression is used more in the real life as compared to the linear regression. Read more »

Procedure and interpretation of linear regression analysis using STATA

Linear regression analysis is conducted to predict the dependent variable based on one or more independent variables. The basic regression equation is:

Finding impact of independent variable on dependent variable Read more »

Importing data to STATA

STATA comes with a set of sample data files. This helps the learner in understanding how different set of tests can be applied to single data. For the purpose of understanding this module I will be using auto.dta and will be applying some tests to this data. Read more »

Examples of threats to internal and external validity in a research

In my previous article I have discussed how the validity can be ensured with respect to Quantitative and Qualitative analysis. This article discusses the threats to validity (internal and external) irrespective of the approach. Read more »

8-step procedure to conduct qualitative content analysis in a research

A study by Ary et al. (1996) categorized qualitative research/method into two distinct forms. Firstly participant observation, where the researcher is a participant of the study. Secondly non-participant observation, where the researcher observes but does not participate. It is in this non-participant observation where one can use the content analysis approach. Read more »

Importance of research approach in a research

Research approach is a plan and procedure that consists of the steps of broad assumptions to detailed method of data collection, analysis and interpretation. It is therefore, based on the nature of the research problem being addressed. Research approach is essentially divided into two categories:

  1. approach of data collection and
  2. approach of data analysis or reasoning. Read more »

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