Skip to content
Research Article Open access CC BY 4.0

Application of Categorical Data-nested Design of Knowledge & Control Practices of HBV Infection

O. A. P. Otaru, P. N. Ogbonda

Advances in Research · pp. 21–29 · Published 11 Jun 2020

10.9734/air/2020/v21i630210

Abstract

In real-life, most experimental data are presented in frequencies with no underlying metric probably because of some reasons such as less susceptibility to observational errors. Unfortunately, some of these data have been erroneously analyzed resulting to either type I or type II error. The significance of main factor (University) and sub-factor (Faculty) are studied using categorical data in nested classification. The CATANOVA technique used is suitable for mixed design, having some factors crossed and others nested. The study considered frequency data involving response scores of student’s knowledge and control practices of HBV infection using a scale of good, fair and poor. Numerical results revealed that the main factor, University and the sub-factor, Faculty are not significant (p>0.05) in each case. More so, there was poor level of student’s knowledge and control practices of HBV infection which were also found to be significantly (p>0.05) same in Universities.

Frequency nested categorical knowledge practices infection Hepatitis B liver cirrhosis.

Cited by 0

No indexed citations yet.

Article metrics

Real usage data collected on this platform.

0

Page views

0

PDF downloads

0

Outbound clicks

0

Citations

Views by country

Approximate, from request IP at view time — not citizenship or institution. Countries with fewer than 5 views are grouped as "Other".

No views recorded yet.

Traffic sources

Referring site, by host.

No traffic recorded yet.

Views and downloads exclude known bots/crawlers. Citations combines this platform's own DOI-resolved index with each external source's own reported total — see Cited by above for individually listed citing works. Last refreshed 0 seconds ago.