INTRODUCTION TO STATISTICAL MODELLING IN R

More documents

Recommendations

Info

Chapter 10Analysis of a 2-way contingencytableHere we present an analysis of a 4 × 2 contingency table and show 3 different waysof getting the same result.You can check from the log-likelihood function WHY these give the same result.The data given in Table 10.1 were obtained by Prof I.M.Goodyer, as part of a studyon 11-year-old children, to investigate the relationship between ‘deviant behaviour’(no/yes) and several other variables. The results for the variable ‘emotionality’ areshown below (emo=1 meaning low emotionality,... emo=4 meaning high emotionality).Here are my suggestions for the analysis.behaviour no yesemo=1 51 3emo=2 69 11emo=3 28 22emo=4 7 13Table 10.1: Is there a link between emotionality and bad behaviour?a
P.M.E.Altham, University of Cambridge 46that this is the case.Other useful functions for contingency tables arextabs(),mosaicplot(), fisher.test()The last of these 3 functions relates to Fisher’s ‘exact’ test, and makes use of thehypergeometric distribution. It is most often applied to 2 × 2 tables, but R has aversion for an r × s table too.An example added after the Sheffield floods in June 2007The Sheffield flood of March 1864 was a disaster not easily forgotten, and an excellentdescription may be seen at http://www2.shu.ac.uk/sfca including the wholebook ‘A complete history of the great flood at Sheffield on March 11 and 12, 1864’by Samuel Harrison, and also details of the resulting insurance claims. (It is salutaryto note that there was a total of 6987 claims, for a total of £458, 552, of which£273, 988 was paid out. This included £123 11s 2d paid to my great great grandfather,who was a Saw Manufacturer on Kelham Island.) You may like to considerthe contingency table given as Table 10.2, which shows Sheffield properties affectedby the flood. The row names are respectively abbreviations of the followingTotally Destroyed Partially Destroyed Flooded OnlyManufactories 12 25 80Mills 4 17 22Workshops 17 11 135Shops 3 15 451Dwellings 39 376 4096Malthouses 2 22 162Other 53 11 71Table 10.2: Damage to property in the Sheffield flood of 1864Manufactories, tilts etcRolling, grinding, corn and other millsWorkshops, warehouses, store rooms etc,Drapers’, grocers’ and other sale shopsDwelling housesMalt houses, breweries, public and beer housesOther buildings.Note added June 2006.Julian Faraway’s new book ‘Extending the Linear Model with R: generalized Linear,Mixed Effects and Nonparametric Regression Models’ (2006) contains the datasetcmobon Social class mobility from 1971 to 1981 in the UK.This gives us the 6 × 6 contingency table describing Social class mobility from 1971to 1981 for 42425 men from the United Kingdom census. The subjects were aged
Page 1: INTRODUCTION TO STATISTICALMODELLIN
Page 4 and 5: PrefaceR is available as Free Softw
Page 6: Chapter 1Getting started: books and
Page 9: Chapter 2Ways of reading in data, t
Page 13 and 14: P.M.E.Altham, University of Cambrid
Page 29 and 30: Chapter 5A 2-way anova, how to set
Page 33 and 34: Chapter 6A 2-way layout with missin
Page 39 and 40: Chapter 8The space shuttle temperat
Page 45: P.M.E.Altham, University of Cambrid
Page 59 and 60: Chapter 12Fisher’s exact test, 3-
Page 63 and 64: Chapter 13Defining a function in R,
Page 65 and 66: zbP.M.E.Altham, University of Cambr
Page 83 and 84: Chapter 18Crime and unemployment: a
Page 87 and 88: Chapter 19Maximising a multi-parame
Page 97 and 98:
P.M.E.Altham, University of Cambrid
Page 99 and 100:
Page 101 and 102:
Page 103 and 104:
Page 105 and 106:
Page 107 and 108:
Chapter 22Brief introduction to Sur
Page 109 and 110:
Page 111 and 112:
IndexAIC, 36.Rdata, 10.Rhistory, 10
show all

INTRODUCTION TO STATISTICAL MODELLING IN R

Create successful ePaper yourself

Delete template?

Save as template?