Data analysis in qualitative research

Related slideshares at ative data n nigatu haregu, phd hed on mar 6, presentation summarizes qualitative data analysis methods in a brief manner. Read and use for your qualitative you sure you want message goes er, university of technology and education, ho chi minh city, viet sity of presentation is definitely helpful for my knowledge of conducting a qualitative research project. G/ational development program m&e,coordinator, trainer, data manger, research assistant, a nice slide of presentation. Hope you will add more on qualitative coding and you sure you want message goes ion specialist _unicef nutrition specialist _ ant professor, leed ative data e of the presentationqualitative researchqualitative dataqualitative analysisqualitative softwarequalitative reporting ative research is qualitative research? Pope & mays bmj 1995;311:42-45 ions of qualitative methodsunderstanding context• how economic, political, social, cultural, environmental and organizational factors influence healthunderstanding people• how people make sense of their experiences of health and diseaseunderstanding interaction• how the various actors involved in different public health activities interact each other vs quan: basic differences qualitative quantitativepurpose to describe a situation, to measure magnitude-how gain insight to particular widespread is a practice... No pre-determined pre-determined response response categories categories, standard measuresdata in-depth explanatory data wide breadth of data from large from a small sample statistically representative sampleanalysis draws out patterns from tests hypotheses, uses data to concepts and insights support conclusionresult illustrative explanation & numerical aggregation in individual responses summaries, responses are clusteredsampling theoretical statistical vs quan: analytic approaches quantitative qualitativeresearch question fixed/focused broader, contextual, flexibleexpected outcome identified in usually not predefined, advance emergent research questionhierarchy of phases linearity circularconfounding factors controlled during searched in the field design & analysistime dimension slower rapid to slower vs quan: data collection method quantitative qualitativesampling random sampling open ended and less structured protocols (flexible)tools structured data depend on interactive collection instruments interviewsresults produce results that produce results that give generalize, compare and meaning, experience and views summarize for combining qual-quan methods qual-quan combining models sequential use model concurrent use modelqual-quan quan-qual quan qual quan qual model model model model ant concepts in designing qualitative researchconcept descriptionnatural setting participants are free from any control & data are collected in their natural environmentholism the whole is more than the sum, take magnitude of contextual factors in to accounthuman as a researcher is involved in every step being responsive,research flexible, adaptive and good listenerinstrumentemergent design study design emerges as further insights are gained through data collection and analysissaturation or a stage where additional interview or observation is notredundancy believed to add new information-enough is enough!

Data analysis procedures in qualitative research

Qualitative study designsstudy design descriptionethnography portrait of people- study of the story and culture of a group usually to develop cultural awareness & sensitivityphenomenology study of individual’s lived experiences of events-e. The experience of aids caregrounded theory going beyond adding to the existing body of knowledge-developing a new theory about a phenomenon-theory grounded on dataparticipatory action individuals & groups researching their own personalresearch beings, socio-cultural settings and experiencescase study in-depth investigation of a single or small number of units at a point (over a period) in time. Evaluation of s service ng in qualitative research • to generate a sample which allows understanding the social process aim of interest • purposive sampling- selection of the most productive sample to answer the research questiontechnique • ongoing interpretation of data will indicate who should be approached, including identification of missing voices • the one that adequately answers the research question-until new size categories, themes or explanations stop emerging from the data • depend on available time and resources ng techniques in qualitative research snow ball/chain  extreme/deviant  homogeneous  sampling case sampling sampling maximum  convenience  opportunistic variation sampling sampling sampling ative data of qualitative datastructured text, (writings, stories, survey comments,news articles, books etc)unstructured text (transcription, interviews, focusgroups, conversation)audio recordings, musicvideo recordings (graphics, art, pictures, visuals). Data collection methodsmethods brief explanationobservation the researcher gets close enough to study subjects to observe (with/without participation) usually to understand whether people do what they say they do, and to access tacit knowledge of subjectsinterview this involves asking questions, listening to and recording answers from an individual or group on a structured, semi-structured or unstructured format in an in-depth mannerfocus group focused (guided by a set of questions) and interactivediscussion session with a group small enough for everyone to have chance to talk and large enough to provide diversity of opinionsother methods rapid assessment procedure (rap), free listing, pile sort, ranking, life history (biography) ons for qualitative interviewstypes of examplesquestionshypothetical if you get the chance to be an hiv scientist, do you think you can discover a vaccine for hiv? Of qualitative questions• experience: when you told your manager that the project has failed, what happened? Ing transcripttranscribe word by word (verbatim)consider non-verbal expressionstry to do the transcribing yourselfbe patient-time consuming ing metadata(log)project/research titledate of data collectionplace of data collectionid-code of informant(s)research teammethod of data collectiondocumentation type: tape recorder, notesand observations ative analysis is qualitative data analysis?

Data analysis techniques in research

Data analysis (qda) is the range ofprocesses and procedures whereby we move from thequalitative data that have been collected into some formof explanation, understanding or interpretation of thepeople and situations we are is usually based on an interpretative idea is to examine the meaningful and symboliccontent of qualitative data http:///intro_qda/what_is_ ches in analysisdeductive approach – using your research questions to group the data and then look for similarities and differences – used when time and resources are limited – used when qualitative research is a smaller component of a larger quantitative studyinductive approach – used when qualitative research is a major design of the inquiry – using emergent framework to group the data and then look for relationships ative vs quantitative data analysisqualitative quantitative• begins with more general • key explanatory and open-ended questions, outcome variables moving toward greater identified in advance precision as more • contextual/confounding information emerges variables identified and• pre-defined variables are controlled not identified in advance • data collection and• preliminary analysis is an analysis distinctly inherent part of data separate phases collection • analysis use formal statistical procedures for helping the analytical processsummaries: should contain the key points thatemerge from undertaking the specific activityself memos: allow you to make a record of theideas which occur to you about any aspect ofyour research, as you think of themresearcher used in qualitative data analysistheory: a set of interrelated concepts, definitions and propositionsthat presents a systematic view of events or situations by specifyingrelations among variablesthemes: idea categories that emerge from grouping of lower-leveldata pointscharacteristic: a single item or event in a text, similar to anindividual response to a variable or indicator in a quantitativeresearch. It is the smallest unit of analysiscoding: the process of attaching labels to lines of text so that theresearcher can group and compare similar or related pieces ofinformationcoding sorts: compilation of similarly coded blocks of text fromdifferent sources in to a single file or reportindexing: process that generates a word list comprising all thesubstantive words and their location within the texts entered in to aprogram ples of qualitative data analysis1. Exceptional cases may yield insights in to a problem or new idea for further inquiry es of qualitative data analysis• analysis is circular and non-linear• iterative and progressive• close interaction with the data• data collection and analysis is simultaneous• level of analysis varies• uses inflection i. This was good”• can be sorted in many ways• qualitative data by itself has meaning, i. Apple” ng, collecting and thinking model think  collect  about  things things notice things process of qualitative data analysisstep 1: organize the datastep 2: identify frameworkstep 3: sort data in to frameworkstep 4: use the framework for descriptive analysisstep 5: second order analysis 2: identify a framework• read, read, read... Identify a framework – explanatory – guided by the research question – exploratory-guided by the data• framework will structure, label and define data• framework=coding plan 3: sort data in to framework• code the data• modify the framework• data entry if use computer packages http:///intro_qda/how_what_to_ 4: use framework in descriptive analysis• descriptive analysis – range of responses in categories – identify recurrent themesstop here if exploratory research 5: second order analysis• identify recurrent themes• notice patterns in the data• identify respondent clusters – search for causality – identify related themes• build sequence of events• search data to answer research questions• develop hypothesis and test of qualitative analysis• content analysis• narrative analysis• discourse analysis• framework analysis• grounded theory http:/// t analysis• content analysis is the procedure for the categorization of verbal or behavioural data for the purpose of classification, summarization and tabulation• the content can be analyzed on two levels – descriptive: what is the data?

Data analysis methods in qualitative research

Http:///guides/research/content/ ive analysis• narratives are transcribed experiences• every interview/observation has narrative aspect-the researcher has to sort-out and reflect up on them, enhance them, and present them in a revised shape to the reader• the core activity in narrative analysis is to reformulate stories presented by people in different contexts and based on their different experiences http:///garson/pa765/ gies for analyzing observations• chronology: describe what was observed chronologically overtime, to tell the story from the beginning to the end• key events: describing critical incidents or major events, not necessarily in order of occurrence but in order of importance• various settings: describe various places, sites, settings, or locations in which events/behaviours of interest happen• people: describing individuals or groups involved in the events• process: describing important processes (e. Control, recruitment, decision-making, socialization, communication)• issues: illuminating key issues – how did participants change y in qualitative studiescriteria issues solutioncredibility truth value prolonged & persistent observation,(=internal validity) triangulation, peer-debriefing, member checks, deviant case analysistransferability applicability thick description, referential adequacy,(=external validity) prevention of premature closure of the data, reflexive journaldependability consistency dependability audit(=reliability) reflexive journalconformability neutrality conformability audit(=objectivity) reflexive journal http:///intro_qda/qualitative_ ative software ng and using computer software• it is possible to conduct qualitative analysis without a computer• concerns: relying too much on computers shortcuts will impede the process by distancing the researcher from the text• advantages: ease the burden of cutting and pasting by hand, and produce more powerful analysis by creation and insertion of codes in to text files, indexing, construction of hyperlinks, and selective retrieval of text segments ative analysis with softwares• with qualitative softwares, your workflow will be similar, but each step will be made easier by the computer’s capability for data storage, automated searching and display. You can use text, picture, audio and video source files directly• you can assign codes manually (autocode) to any section of text, audio or video or part of a picture• analysis is easy with the report feature, where you can select a subset of cases and codes to work with, choose what data to use, and sort your reports automatically http:/// of computer software in qualitative studies1) transcribing data2) writing/editing the data3) storage of data4) coding data (keywords or tags)5) search and retrieval of data6) data linking of related text7) writing/editing memos about the data8) display of selected reduced data9) graphic mapping10) preparing reports http:///intro_caqdas/what_the_sw_can_ to choose software - key questionstype and amount of datatheoretical approach to analysistime to learn vs time to analyzelevel of analysis (simple or detailed)desired “closeness” to the dataany desired quantification of resultsindividual or working as a teampeer software support availableany cost constraints (weitzman and miles 1995; lewins and silver 2005). G a qualitative report g qualitative reportqualitative research generates rich information- thus deciding where to focus and the level of sharing is very challenging. Http:///michael/qual_ g ready to write• must come close to the point of maturation – be aware of resource constraints and sponsors interests• organize your materials – list of codes – summary device: tables, thematic structure• writing a chronicle (“writing it out of your head”) ng a style and focus• format • research report • scientific research article • report to donor • field report • evaluation report... Focus – academic: conceptual framework/theories, methodology and interpretation – practitioners: concrete suggestions for better practice, policy recommendations – lay readers: problem solving, reform on practice/policy ions in the report format• problem-solving approach (problem-based)• narrative approach (chronological)• policy approach (evidence-based)• analytic approach (theory/conceptual framework based) ing qualitative research• typically use quotes from data – descriptive – direct link with data – credibility• ways to use quotes – illustrative – range of issues – opposing views ing without quotes• list range of issues• rank or sequence issues• describe types of behaviour, strategies, experiences• report proportions (most, many, the majority)• flow diagrams: decision-making, event sequencing etc retation• interpretation is the act of identifying and explaining the core meaning of the data• organizing and connecting emerging themes, sub-themes and contradictions to get the bigger picture-what it all means – think how best to integrate data from multiple sources and methods• make generalization-providing answers to questions of social and theoretical significance• ensuring credible or trustworthy interpretations rd report format1.

Data analysis techniques in qualitative research

References ng the basics of course - linkedin course - linkedin r tech tips course - linkedin tative data ative data analysis (steps). Data analysis r 10-data analysis & mae nalzaro,bsm,bsn, analysis analysis tation, analysis and interpretation of sent successfully.. References heavin the thinkable course - linkedin course - linkedin oint 2016 essential course - linkedin tative data ative data analysis (steps). You should still be able to navigate through these materials but selftest questions will not 9 : introduction to 1: introduction to 2 research and the voluntary and community 3 primary and secondary 4 research 5 quantitative 6 qualitative 7 ethics and data 8 presenting and using research findings. Analysing qualitative research analysis of qualitative research involves aiming to uncover and / or understand the big picture - by using the data to describe the phenomenon and what this means. Both qualitative and quantitative analysis involves labelling and coding all of the data in order that similarities and differences can be recognised.

Data analysis approach in qualitative research

Responses from even an unstructured qualitative interview can be entered into a computer in order for it to be coded, counted and analysed. The qualitative researcher, however, has no system for pre-coding, therefore a method of identifying and labelling or coding data needs to be developed that is bespoke for each research. Which is called content t analysis can be used when qualitative data has been collected through:Content analysis is '... Procedure for the categorisation of verbal or behavioural data, for purposes of classification, summarisation and tabulation. Content can be analysed on two levels:Basic level or the manifest level: a descriptive account of the data i. This is what was said, but no comments or theories as to why or level or latent level of analysis: a more interpretive analysis that is concerned with the response as well as what may have been inferred or t analysis involves coding and classifying data, also referred to as categorising and indexing and the aim of context analysis is to make sense of the data collected and to highlight the important messages, features or with wimba need to analyse the data from our qualitative research study in order sense of it and to make accessible to the researcher (and people who report of the research) the large amount of rich textual data that has evidence obtained from the ned with the organisation and the interpretation of information ( numerical information, which is generally the preserve of ch) in order to discover any important underlying patterns and is involves such processes as coding (open,Axial, and selective), categorising and making sense of the essential meanings of the researcher works/lives rich descriptive data, then common themes stage of analysis es total immersion for as long as it is needed in order to a pure and a thorough description of the this is concerned with sation and the interpretation of information (other than ation, which is generally the preserve of quantitative research] to discover any important underlying patterns and qualitative research requires slightly different methods of data analysis:The constant is the process that we use in qualitative research in which any ted data is compared with ted data that was collected in an earlier is a continuous ure, because theories are formed, enhanced, confirmed, or even a result of any new data that emerges from the study.

Way in which data can ntly compared throughout a research study is by means of coding:Coding - open coding is the first organisation of the data to try some sense of - axial coding is a way of interconnecting the - selective coding is the building of a story that the end of these processes, it that one has achieved the production of a set of theoretical propositions. Data analysis is the process in which we move raw data that have been collected as part of the research study and use provide explanations, understanding and interpretation of the phenomena,People and situations which we are aim of analysing qualitative data is to examine gful and symbolic content of that which is found within. This, of course, many ways be dictated by the methodology and data collection methods that already decided to look at the data analysis that is described in the e we are using as a ncbi web site requires javascript to tionresourceshow toabout ncbi accesskeysmy ncbisign in to ncbisign l listmalays fam physicianv.