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Analysis of Qualitative Data(質性資料分析 )

Social Research Methods2113 & 6151Spring, 2007

May 15~22, 2007

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Four parts

• Comparing Methods of Data Analysis

• Coding and Concept Formation

• Analytic Strategies for Qualitative Data

• Other Techniques

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Comparing data analysis methods

Similarities of quantitative and qualitative data analysis (質性與量化資料分析的相似處 )

• inferring from the empirical details of social life– To infer (推論 ): based on evidence

• Involving a public method or process (公開的方法或過程蒐集資料 )

• Comparison is central (資料分析的重點在於比較 )– Compare evidence to locate patterns (similarities and

differences)• Striving to avoid errors, false conclusions, and m

isleading inferences (避免各項錯誤 )

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Comparing data analysis methodsQuantitative data analysis

• A specialized, standardized set of techniques

• Begin to analyze data after data collection and processing

• Test hypotheses• Social life measured

by using numbers, then using statistics

Qualitative data analysis

• less standardized, often inductive

• Begin analysis while collecting data

• Create new concepts and theory

• Data relatively imprecise, diffuse, and context-based

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Explanations and Qualitative Data

• Developing explanations that are close to concrete data and contexts (解釋接近具體的資料與脈絡 )– Less abstract theory grounded in concrete details, se

nsitive to context, could be causal

• Either highly unlikely or plausible– Can eliminate an explanation b showing contradictory

evidence

• Best to make theories and concepts explicit (最好讓理論和概念明確 )

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Coding and Concept Formation

• Conceptualization: grounded in data– Concept formation begins during data collectio

n– Data analysis: organizing data into categories

on the basis of concepts/themes, i.e., coding

(根據概念或是主題，把資料分成不同類別來分析 )

– Ideas and evidence mutually interdependence

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Coding in Qualitative Data Analysis

• Coding: organizing the raw data into conceptual categories and create themes/concepts (編碼 : 將原始資料依概念類別整哩，以發展出新的主題或概念 ) – Difficult for novice researchers

• Two simultaneous activities: – Mechanical data reduction (資料縮減 )

• Reducing large amount of data into manageable piles• Quickly retrieve parts of data

– Analytic categorization of data (資料依分析類別整理 )

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Three types of coding

Open coding (開放式編碼 )

Axial coding (主軸式編碼 )

Selective coding (選擇性編碼 )

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Open Coding

• Open coding: performed during a first pass through collected data (剛開始蒐集資料的第一階段使用開放式編碼 )– Reads all field notes or other data– Writes a preliminary code label on the edge of

a record

• Brings themes to the surface from deep inside the data (將主題從資料內部浮現出來 )

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Axial Coding

• A “second pass” through the data, already have an organized sets of codes/concepts

• To review and examine initial codes: think about linkages between concepts (回顧檢視先前的編碼 : 思考概念間的連結 )– Organize themes and identify the axis of key concepts– Ask about causes and consequences, conditions and i

nteractions, strategies, and processes, – Cluster categories/concepts (將概念或類別群聚 )

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Selective Coding

• Scan all the data and previous codes, look selectively for cases for comparisons and contrasting (再一次地掃描資料與先前的編碼，選擇性地檢視能進行比較或對比的個案 )

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Coding and Concept Formation

• Analytic memo writing (撰寫分析備忘錄 ): discussion of thoughts and ideas about the coding– A link between the concrete data or raw evide

nce and theoretical thinking

• Outcropping (表面事實 ): events on the surface– Events as presenting deeper structural relatio

ns

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Analytic memo writing

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Analytic Strategies for Qualitative Data

• NOTE: data analysis means a search for patterns (類型 ) in data

• Ideal types (理念型 ): models or mental abstractions of social relations/processes– Pure standards used for comparison– To contrast the impact of contexts and as anal

ogy

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Analytic Strategies for Qualitative Data

• Successive approximation (連續的近似 ): repeated iterations between the empirical data and the abstract concepts, adjusting theory and refining data collection each time

• The illustrative method (舉例法 ): taking theoretical concepts and treating them as empty boxes to be filled with specific empirical examples and descriptions

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Analytic Strategies for Qualitative Data

• Analytical comparison (分析比較 ): developed by John Stuart Mill; need multiple cases– Identifying many factors for a set of cases, sor

ts through logical combinations of factors, and compares them across cases

– Nominal comparison because factors most often are nominal

– A few cases & intensive data analysis

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Analytical comparison (分析比較 )Category II: Milk Segregation

Processor Characterstics

Processor

ID

Type of

Processors

Patron

Size

Farmers

Certified

Products labeled

as

“rBGH-Free”

Certified

Products

1006 Milk Supplier Large Yes Yes -

1016 Milk Supplier Large Yes n.a. -

1031 Milk Supplier

Medium

Small Yes n.a. -

1020 Milk Supplier Small Yes Yes -

1026

Milk Supplier/

Manufacturer Small Yes n.a. Cheese

1015 Manufacturer

Medium

Small Yes No Milk

1023 Manufacturer

Medium

Small Yes No Milk

1017 Manufacturer

Medium

Large Yes Yes Milk

1011 Manufacturer Large n.a. n.a. Milk

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Analytic Strategies for Qualitative Data

• Analytical comparison: method of agreement and method of difference

• Method of agreement (一致法 )– What is common across cases, using a proce

ss of elimination

• Method of difference (差異法 ): 1) locating cases similar in many respects but different in a few crucial ways, 2) focusing on the differences among cases

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Analytic Strategies for Qualitative Data

• Narrative Analysis (敘事分析 ): a historical writing as well as a types of qualitative data analysis

• Narrative: multiple meanings– A narrative (as raw data): referring to the condi

tion of social life– Narrative text: a story-like format people apply

to organize and express meaning in social life– Narrative inquiry: method of investigation and

data collection

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Narrative Analysis

• Narrative: multiple meanings– A narrative style: “storytelling” ; blending desc

ription, empathetic understanding, and interpretation

– Narrative a a method of analyzing data– Narrative analysis: path dependency, periodiz

ation, & historical contingency

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Analytic Strategies for Qualitative Data

• Negative Case Method (反面個案方法 ): what is not explicit in the data; what did not happen– Systematically examining the absence of what

is expected– A single negative case can tell a lot about wh

at theories did not take into account

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Other Techniques

• Use maps or diagrams to summarize your points and illustrate social relations– Network analysis: use maps to show

connections among a set of people, events, places

– Diagrams/charts: organize ideas and investigate relations in the data

– Maps: see spatial relations and supplement/reinforce results from other data

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Software for Qualitative Data

Used more in recent years

several choices, select wisely

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Qualitative Data Analysis

• Qualitative data more difficult to deal with than numerical data

• Need careful reading of your data (mostly texts): coding and writing analytic memos

• Learn some generic and particular techniques

• Writing skills are critical in presenting qualitative data