Handling qualitative data a practical guide

SECOND EDITION

HANDLING

QUALITATIVE

NGUYEN

OC LIEU

LYN RICHARDS

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Handling

Qualitative Data

DAI H (r J l-A. I ^ IJ Y E N

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Handling

Qualitative Data

A Practical Guide

Second Edition

Lyn Richards

(DSAGE

Los Angeles | London | New Delhi

Singapore | Washington DC

© Lyn Richards 2009

First edition published 2005

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o

Mixed Sources

SUMMARY OF CONTENTS

Introduction 1

PARTI SETTINGUP 9

1 Setting up your project 11

2 Making qualitative data 33

3 D ata records 55

PART II W O R K IN G W ITH T H E DATA 71

4 U p from th e data 73

5 Coding 93

6 H andling ideas 115

PART III M A K IN G SENSE O F YO UR DATA 131

7 W h at are you aiming for? 133

8 Searching th e data 155

9 Seeing a w hole 171

10 Telling it 191

CONTENTS

Preface x

Acknowledgements xiii

Introduction 1

Starting points 1

The shape of this book 5

PART I SETTING UP 9

1 Setting up your project 11

Purpose, goal and outcom e 12

Designing the project 13

You and your data 20

Logging your design 25

Learning your software 27

To do 30

Suggestions for further reading 31

2 M a k in g q u a l ita tiv e J u t u 3 3

U nderstanding data 33

Preparing to 'm ake' data 39

Purposive data making 47

D ata about your project (and you) 48

To do 52

Suggestions for further reading 52

3 D ata records 55

W hat will th e records be like? 56

H ow big should a data record be? 58

H ow will th e records be stored? 61

W hat information will be stored w ith the record? 64

W hen can you start analysing? 68

To do 69

Suggestions for further reading 70

PART II W O R K IN G W ITH THE DATA 71

4 U p from the data 73

M eeting data 75

W here do your ideas go? 79

Handling your discoveries 82

Drawing it - th e early uses o f m odels 83

Revisiting design 83

Revisiting and reviewing records 85

W riting it 88

Up to the category 89

To do 89

Suggestions for further reading 90

5 Coding 93

Q ualitative and quantitative coding 93

W hat can you do w ith coding? 95

Ways of coding in a qualitative project 96

Revisiting the coded data 104

Coder reliability in qualitative research 108

Avoiding th e coding trap 109

Establishing your personal data processing style 110

W riting about coding 111

To do 112

Suggestions for further reading 112

6 Handling Ideas 115

O rganization and creativity 116

Catalogues of categories 117

W riting your ideas 127

To do 129

Suggestions for further reading 129

PART III M A KING SENSE O F YOUR DATA 131

7 W hat are you aim ing for? 133

W hat are you seeking? 134

W hat can you achieve? 136

W hat w ould be satisfactory? 138

W hat m ight it look like? Possible outcom es 139

How will you know w hen you get there? 143

How will you know if it is good enough? 147

To do 153

Suggestions for further reading 153

CONTENTS viii

8 Searching the data 155

Moving forward 155

The data-theory process 157

Searching coding 159

Searching the tex t 164

Building on searches 166

Reporting searches 167

To do 168

Suggestions for fu rth er reading 168

9 Seeing a whole 171

Seeing w hat’s there - and w h at’s not there 171

Ways of seeing 172

A ccounting for and validating your ‘seeing’ 185

To do 189

Suggestions for fu rther reading 189

10 Telling it 191

Start w ith w hat you have w ritten 192

W hat if it w o n 't write? 195

Planning a qualitative report 197

W hat about validity and reliability? 199

Using your data 201

Reports that d o n ’t w ork 203

Concluding your study 206

To do 207

Suggestions for further reading 207

References 208

Index 211

ix CONTENTS

PREFACE

M ethodologists may decry it, and experienced researchers normally deny it,

b u t researchers approaching qualitative research are highly likely to m eet data

before they m eet m ethod.

This book is designed to assist w hen qualitative data have to be handled. In

decades of helping researchers worldwide, I have learned th at those w ho come

to qualitative research 'data first’ rather than ‘m ethods first’ are often th e most

m otivated and critical. But they are also held back by lack of preparation in

ways to handle data records, and by messages about the m ystique and difficulty

of doing, or even thinking about doing, qualitative research. So too, often, are

those who have had some training in the study of the theory o f m ethods -

methodology. How ever adequate their understanding of th e philosophy behind

w hat they are trying to do, they may have no practical idea of how they would

handle data if they ever had some.

This book starts there. It is, therefore, very different from m ost texts on

qualitative m ethods.

Firstly, it is about handling data - working w ith data in order to produce

adequate and useful outcomes. It’s amazing how little o f th e m ethodological

lite ra tu re is in th is are a. E v e n te x ts w ith title s a b o u t 'a n a ly sin g ' o r ‘d o in g ’ q u a l￾itative research spend considerably m ore tim e on ways of m aking data than on

w hat you w ould do w ith such data if you ever actually had any. A nd from the

perspective of those w ho have to do it, texts addressing th e critical issues of

relation betw een researcher and record are often inaccessibly high up in the

m isty m ountains of academic discourse.

Secondly, this book steers a cautious course around those mountains, while

urging th at the researcher m ust be aware th at they are there. An irony o f our

tim e is th at just as qualitative research has becom e acceptable and required

across m ost areas of research practice in social enquiry, it has been shrouded

in clouds of debate about reality and its representation. These debates enthral

and entice those o f us w ith tim e and training to engage in them , b u t send a

strong message to practitioners th at qualitative research is possibly a futile

endeavour from th e start. It seems to m e that, since the w orld undoubtedly

needs good qualitative research (and does not need bad), all researchers

require assistance in designing projects and handling data thoughtfully and

successfully. This book is for the m any (out of and inside academ ia) who have

neither access to courses on epistemological issues nor tim e to do them , yet

are conronted w ith a project and wish to learn how they can best deal with

it. My vork with researchers across areas o f practice and disciplines has con￾vinced n e that the majority of highly principled and m otivated practitioners

are bypssed by a literature em bedded in the requirem ent th at they under￾stand aid confront th e detail of academic debates before they make a move.

T hey nted practical, accessible and informed advice on how to do their task

well, relecting on w hat w ould be a credible account and producing one.

Thirdy, the book covers neither the range of qualitative m ethods nor how

differert m ethods derive from different epistemological positions. Instead, it

daringh assumes th at handling data well and producing a good research o u t￾com e cbes not require knowing the range and rules o f particular m ethods.

M ost tects start w ith the assumption th at qualitative data are accessible only

via a reearched understanding of all or some methodologies, and th at a pro￾jec t m ist be located w ithin a coherent methodology.

I stared there too and I retain a com m itm ent to w hat I term m ethodologi￾cal fit, ihe ways in w hich question, data, ways of handling data, ways of con￾structin’ an outcom e and ways of justifying it fit together. I w rote about that

in Reaane First (Richards and Morse, 2007). In this book, however, I aim to

convey this fit to researchers who may not have the tim e or opportunity

to learri from or engage in m ethodological debates bu t do w ant to do justice

to data. And I aim to encourage them , w hatever their m ethodological persua￾sion, to reflect on th eir relationship to their project and their data.

Fourlhly, you will find here no specification of the rules for working in any

particular m ethod. Texts that do address the tasks of data handling usually do

so from w ithin one m ethod, providing detailed rules for the processes associ￾ated with, for exam ple, a particular version o f discourse analysis, grounded

theory )r phenom enology or preparation tor an ethnography. Such learning

will of ;ourse provide a firm basis for research, and as a teacher and w riter I

have se: it as a goal for students. This book consistently urges the reader who

can do so to pursue literature within the appropriate m ethod for their study.

B ut it also assumes th at there is m uch to be learned for any study from m any

methocs. M ethodological ghettoism serves neither those outside nor those

working inside the closed world of a particular m ethod. And m oreover it

assumes that all qualitative researchers need basic skills for handling data, and

these skills are used across m ethods. M ethodological fit and skills for handling

data cai be learned by those working in any particular m ethod or by those

w ho are not steeped in th e literature particular to one m ethod. All novice

researchers need pragmatic, inform ed and understandable assistance in the

processes of making useful data records, in handling and working w ith the data

on the 'oad to a good analysis, and in showing th at it is good.

And finally, this book assumes that you will use com puter software when

handling qualitative data. M ost researchers use com puters in at least some

context and those w ho do not are clearly restricted. For m ethods texts to treat

com puter handling o f qualitative data as an optional extra (m ost do), makes it

xi PREFACE

far harder to discuss practically w hat we can now do w ith data. T h at’s because

qualitative software has transform ed the tasks of handling qualitative data.

This book advises on techniques th at can be done on paper alongside ones that

can be undertaken only by using software. It warns o f and tackles the chal￾lenges o f computer-assisted handling of data, and issues to be considered. But

it assumes you will use software. It does not teach any particular software -

learning software is another task. N or does the text assume th at any particu￾lar software package is to be used. A decade of my research life was spent in

the fascinating tasks of software developm ent and teaching research strategies

w ith software. O f course, this work is reflected in the advice given, since it’s

in th at context th at I have learned of the challenges and pitfalls this book aims

to rescue you from, and developed m any o f th e strategies it suggests. And, of

course, th e software I have helped develop (QSR N U D IST and NVivo)

reflects the m ethods I teach and the approaches I take to data. But I now have

no connection w ith a software company, and you can use this book with no

com puter software (if you must!) or w ith any specialist software. W here the

techniques described require software, this is noted, as are the few places

w here the techniques suggested are particular to one software package. W here

challenges are greater, or risks higher, because o f w hat you can do w ith soft￾ware, this too is discussed.

Each o f these goals has been expanded in the new w ebsite accompanying

this second edition: www.sagepub.co.uk/richards. There are tw o parts to the

website - ‘M ethods in Practice’ and ‘Q ualitative Softw are'. The first is designed

to offer, as few published accounts do, a vivid picture o f qualitative research

as it happens. There you will find a set of project accounts giving brief but

detailed stories of research experience - w hat really did occur, w hat worked

and the strategies developed to deal w ith challenges. T he second part advises

on Q ualitative Software. Because no software is ever static, and th e needs of

researchers are dynamic and varied, the website will be regularly updated.

This book is w ritten in the conviction that handling qualitative data well beats

handling them badly, and that it can be done. If you are approaching qualitative

m ethods via data, you will not be burdened here with a message that this is

morally bad or practically unwise. By using good tools and by learning simple

skills, novices can always achieve new understanding from data. Many readers

will wish to do no m ore than this. Some may go on to learn the varieties and

rules of different qualitative m ethods and to participate in the discussions of

w hat they represent. O thers will go on to approach positively the puzzles of

qualitative data, to m eet the challenge of sensitively managing larger bodies of

m ore complex data records, and to enjoy the accessible achievem ent of making

sense of a ‘real’ project. O n finishing this book, your data records may not be

fully accessible and analysed, bu t th e goal is to end this book, and the first stage

of a real project, with the knowledge that access and analysis are achievable.

Lyn Richards

PREFACE xii

ACKNOWLEDGEMENTS

In preparing th e second edition of this book, I have been greatly helped by

fedback from students, teachers and researchers around the world, and from

thi editorial team at Sage and their anonymous reviewers - my thanks to all.

One them e was dom inant amongst the responses to the book, as in the sto￾rie from researchers I had taught and helped in 20 years of teaching qualitative

mehods in academia and outside, across countries and disciplines, and all levels

of eniority and experience. This was the difficulty novices find in picturing what

it vould be like to be there, doing a qualitative project. I was encouraged by this

fedback, and by several close colleagues, in pursuing a maverick project I'd

tal:ed of for years - putting together an informal body of accounts of research

exierience, accessible online. Unlike m ost refereed publications and thesis

chpters, such a website could tell it as it is, with live accounts of w hat really

happened and w hat it was really like to face the challenges, how ways around

obtacles were devised, w hat worked and w hat didn't and the extraordinary

exierience of arriving at an adequate account of your data.

/ly thanks to those who backed me in this project, to Sage for seeing it as not

jus ambitious bu t useful, to the many who responded to the call for contribu￾tiois b u t fo r o n e reaso n o r a n o th e r w e re tu rn e d away, and a b o v e all to th e te n

resarchers who finally ran the whole course. It wasn’t an easy task (or for many

acdemics, a familiar one) to write succinctly, briefly, honestly and clearly about

the real story of a project. I greatly appreciate their persistence in reworking

drfts, their tolerance in accepting my critical editing and suggestions and my

gols for the project. The outcom e is a unique research resource, and a good read.

w rote this book for all the researchers I have tried to help around the

gloe, in decades of university teaching at undergraduate and graduate level,

th<n workshop teaching and project consultancy. They taught m e to set aside

asum ptions about research goals and experience that make sense only in

acxlemia (and possibly, now, not there). I also learned new practical ways of

ta(kling the m yths and m onsters o f qualitative methods, and discovered or

in'ented techniques th at worked for those confronted w ith data and th e task

ofio in g justice to messy records.

rhis book was dream t long back. I kept thinking, as the acceptability o f qual￾itaive research grew, and I tried to help researchers with im portant questions

anl no training, that a straightforward text w ould appear to show researchers

hov to handle data. As I waited, both teaching and literature increasingly