Update README.md

README.md

@@ -1 +1,37 @@
-# daDoctoR
+# Intro
+
+I try my best to share my basic workarounds in R to more effectively do statistical research. Feel free to be inspired or comment.
+
+## Further research
+
+In need of a suitable function to perform the chi-squared test of Hardy-Weinberg-equillibrium in my study poppulation, I ended up writing my own. It also contains a few summarise functions. This is actually the function I am most proud of, as it represents an actual universal test for both bi- and triallelic sustems in non-sexcromosome genes.
+
+### Genotype distribution testing
+- hwe_allele.R -- requires input in the form of two vectors with alleles listed
+- hwe_geno.R -- requires input as numbers of each genotype (mm, mn, nn for biallelic systems and mm, mn, nn, mo, no, oo for triallelic)
+- hwe.sum.R -- summarising tests for genotypes grouped by af factor. Performs HWE test for each group and returns neatly formatted distribution for easy copy-pasting to print. No comparisons of groups. Use the oddsratio or chisq.test.
+
+### Formatting large data frames
+- col_fact.R -- formatting columns as factor for names containing text elements of a vector provided. Labels or levels can be provided.
+- col_num.R -- formatting columns as numeric for names containing text elements of a vector provided.
+
+### Bivariate logistic regression analyses
+- rep_glm.R -- for a stepwise gating regression approach this provides several bivariate logistic regression analyses for columns of a dataframe specified by af vector of the format c(). Use the dput() to obtain names of dataframe in correct format.
+- cie_test.R -- Analysis of change in estimate approach with specified cut set at 10 % as standard.
+
+
+## Research year
+
+This is my first attempt at creating something usefull for openly sharing. In my work as a research year student through Aarhus University, Denmark at Aarhus University Hospital, Denmark, I've been introduced to working in the programming language R.
+During this work I've come accross a few problems apparently unique for the work with data from the Danish medical databases. To analyse the data in R I've had to rewrite some commands and to write my own, so I thought that I should share them here for others to take advantage of. Nothing fancy, but hopefully you can skip af few steps on your way through data analysis.
+These functions are forked from my original uploads as drgammelgaard.
+
+
+For a start I've uploaded five commands for extracting data from cpr-numbers:
+- age_calc_function.R
+- cpr_check_function.R
+- cpr_sex_function.R
+- date_convert_function.R
+- dob_extract_cpr_function.R
+
+All of these commands are written to work with the Danish Central Person Registry (CPR) numbers of the format ddmmyy-xxxx.