Publications by Dr Gurpreet Singh, Dr Biju Soman
Spatial Epidemiology Hand-on Workshop: IAPSMCON 2024
Introduction The present document is being prepared as a companion handbook to Hands-on workshop on Spatial Epidemiology using R during 51st Annual National Conference of Indian Association of Preventive and Social Medicine (IAPSMCON 2024). Why learn spatial epidemiology? Spatial epidemiology is the description and analysis of geographically i...
39368 sym R (22801 sym/65 pcs) 17 img
Manipulating string variables using stringr package in R
Introduction Mostly, in the data analysis, we are confronted with numeric data. However, for advanced analytics such as text mining or handling text data, orientation to text data management is required. String variables or text data requires pre-processing to carry out meaningful analysis. Data as naive as gender can be obtained in raw data as M...
3285 sym R (5212 sym/55 pcs)
Random number generation using R
Introduction. Random numbers are required to be generated in epidemiology for a multitude of reasons. Some of the common reasons for generating random numbers are 1. To select a random sample of participants in a study. 2. To assign a random number for anonymising study dataset. 3. To assign a random number for allocation concealment. Content...
1434 sym R (825 sym/5 pcs)
Automated bibliography extraction from PubMed using R
To conduct a systematic review/Citation Network Analysis/ Bibliometric analysis, bibliography from databases is required. RISMed package in R helps in automating the process and saves a lot of effort and time of researchers in the process. This code gives a step wise algorithm for automated data extraction from PubMed database Step 1. Load libra...
702 sym R (557 sym/8 pcs)
Handling missing data using R
Intro to the code. Missing values in the dataset need to be handled before analysing datasets. Commonly used approaches are 1. Replacing the missing value with a rationale value which can be mean/ median/ mode/ or a constant 2. Replacing missing value with previous value in the dataset 3. Deleting the missing values (not a preffered option) W...
685 sym R (1726 sym/28 pcs)
Word Cloud formation for text analytics using R
As a common approach to text analytics, word cloud formation is used to summarise textual data. To make a wordcloud, the major steps include:- Creation of a corpus. Corpora are collection of documents containing natural language text. Cleaning of the corpus by removing punctuations, numbers, unnecessary words, etc (as required) Calculation of ...
826 sym R (2401 sym/25 pcs) 1 img
Spatial interpolation using kriging in R
1 Introduction. Spatial interpolation is undertaken to estimate spatial variation in risk of continuous variables. Kriging is among the most common methods used in spatial interpolation of risk of continuous spatial data variables in epidemiology. The present document is an effort to provide introduction on kriging using geoR package in R. Loadi...
7192 sym R (7095 sym/65 pcs) 13 img
A brief introduction to Mathematical Disease Modelling in R
Introduction. The present document has been prepared to provide a brief introduction to infectious disease modelling using free and open source solutions such as “R”. The document is not a complete overview of the infectious disease modelling aspects but provides a jumpstart for interested readers to perform mathematical modelling using R. We...
5602 sym R (7933 sym/15 pcs) 7 img
Spatial Data Visualisation in R
1 Introduction. This markdown file is adapted from week 01 from Applied Spatial Analysis in Public Health online course available from https://hughst.github.io/. We would like to thank the contributors of the course who have provided the datasets and course in open domain. Though the datasets used in this code are downloaded from the gihub reposi...
3622 sym R (6639 sym/42 pcs) 9 img
Estimation of spatial variation in risk using kernel smoothing in R
1 Introduction. Spatial variation in risk estimation is based on type of dataset under consideration. For point spatial data (e.g. case occurence), smoothing methods are performed whereas for continous spatial data (e.g. temperature) interpolation methods are applied. We will be discussing on smoothing method in this code. The present file has...
5913 sym R (4496 sym/36 pcs) 9 img