11. processing and displaying data

KNOWLEDGE FOR THE BENEFIT OF HUMANITYKNOWLEDGE FOR THE BENEFIT OF HUMANITY

RESEARCH METHODOLOGY (HFS4343)

PROCESSING & DISPLAYING DATA

Dr. Dr. MohdMohd RazifRazif ShahrilShahril

School of Nutrition & Dietetics School of Nutrition & Dietetics

Faculty of Health SciencesFaculty of Health Sciences

UniversitiUniversiti Sultan Sultan ZainalZainal AbidinAbidin

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S C H O O L O F N U T R I T I O N A N D D I E T E T I C S • U N I V E R S I T I S U L T A N Z A I N A L A B I D I N

Topic Learning Outcomes At the end of this lecture, students should be able to;

• describe methods for processing data in quantitative

studies

• describe methods for processing data in qualitative

studies

• explain methods of communicating and displaying

analysed data

• demonstrate how to present data in tables

• illustrate different types of graphs to represent data

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Data processing in quantitative studies

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EditingEditing CodingCoding

11stst 11stst •• Developing a code bookDeveloping a code book

22ndnd 22ndnd •• PrePre--testing the code booktesting the code book

33rdrd 33rdrd •• Coding the dataCoding the data

44thth 44thth •• Verifying the coded dataVerifying the coded data

STEPS IN CODING


Editing

• Information from data collection is called ‘raw data’ or

‘data’

• Processing data is to ensure that the data is ‘clean’.

– Editing = process of ‘cleaning’ data

• Identify and minimise errors, incompleteness,

misclassification and gaps in the information from

respondents

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Editing (cont)

• Ways of minimising incompleteness

– By inference

– By recall

– By giving back to the respondent

• Two ways of editing data;

– Examine all the answers to one question or variable at a time

– Examine all the responses given to all questions by one

respondent at a time

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Coding

• Method of coding depends on;

– The way a variable has been measured (measurement scale) in

your research instrument (e.g. if a response to a question is

descriptive, categorical or quantitative)

– The way you want to communicate the findings about a variable

to your readers.

• Responses by respondents can be classified into;

– Quantitative response

– Categorical responses (which may be quantitative or qualitative)

– Descriptive responses (which are invariably qualitative)

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Coding (cont)

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Quantitative or Quantitative or categorical responsecategorical response

CodesCodes

Descriptive responseDescriptive response

Content analysisContent analysis

Identify main themesIdentify main themes

Examine Examine verbatim verbatim

response and response and integrate with integrate with

text text reportreport

Assign code Assign code for each for each

theme and theme and count count

frequencyfrequency

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Steps for coding

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11stst 11stst ••Developing a code bookDeveloping a code book

22ndnd 22ndnd ••PrePre--testing the code booktesting the code book

33rdrd 33rdrd ••Coding the dataCoding the data

44thth 44thth ••Verifying the coded dataVerifying the coded data


Step 1: Developing a code book

• Code book provides a set of rules for assigning

numerical values to answers obtained from

respondents.

• Structure of code book;

– Column 1: identifies the question and its number in the research

instrument for which the information is being coded

– Column 2: refers to the name of variable in SPSS or MS Excel.

Each variable should have a unique name

– Column 3: lists the responses to the various questions and

actual codes of the code book

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Example of a code book

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Column 1Column 1 Column 1Column 1 Column 2Column 2 Column 2Column 2 Column 3Column 3 Column 3Column 3


Step 2: Pre-testing the code book

• Pre-test involves selecting a few questionnaires and

actually coding the responses

– to ascertain any problems in coding

• If any problem arises, change the code book, after the

pre-test.

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Step 3: Coding the data

• Three ways of coding data

– Coding on the questionnaire itself, if space for coding is

provided at the time of constructing the instrument

– Coding on separate code sheets that are available for purchase

– Coding directly into the computer using a program such as

SPSS.

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Step 4: Verifying the coded data

• Select a few research instruments at random and record

the responses to identify any discrepancies in coding.

• Frame of analysis can also be developed at this point to

identify;

– Which variable are we planning to analyze

– How they should be analysed

– What cross-tabulation you need to work out

– Which variables you need to combine to construct major

concepts or to develop indices

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Data processing in qualitative studies

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Identify the main themesIdentify the main themes

Assign codes to the main themesAssign codes to the main themes

Classify responses under the Classify responses under the main themesmain themes

Integrate themes and responses Integrate themes and responses into the text of your report into the text of your report


Possible results from statistical analysis

1. Significant and predicted results

– Easiest to explain

– Results support logical links developed by the

researcher among the framework, questions,

variables and measurement methods.

2. Significant and not predicted results

– If the results are valid – important addition to the

body of knowledge

– Sometimes the researcher believes so strongly in the

theory that he/she does not believe the results

• Convinced that there was a problem in the methodology 15


Possible results from statistical analysis (cont)

3. Non-significant results

– Inconclusive results are the most difficult to explain

– Referred as negative results

– Might be true reflection of reality. New hypotheses?

New body of knowledge?

– Might also due to error due to inappropriate

methodology.

– Do not mean that there are no relationship among

variables or differences between group

• they indicate that the study failed to find any

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Possible results from statistical analysis (cont)

4. Mixed results

– Most common outcome of studies

– Two dependent measures the same variable may show opposite results

• The difference might be due to methodology problems

– May also indicate a need to modify existing theory

5. Unexpected results

– Relationship found between variables that were not hypothesized and not predicted from the framework guiding the study

– Can be used to develop or refine theory and to formulate later studies

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Methods of displaying data

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TextText TablesTables

GraphsGraphs Statistical Statistical measuremeasure


Structure of a table

• Title – table number and describes the type of data

• Stub – sub-categories of variables in y-axis

• Column heading - sub-categories of variables in x-axis

• Body – cells housing of data

• Supplementary notes or footnotes – source, level of

probability, specific notes, general notes

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11

22

33

44

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Structure of a table (cont.)

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Characteristics Male Female p-value a

Age (years)

Body weight (kg)

Height (m)

BMI (kg/m2)

Body fat (%)

Bone mass (kg)

Table 4.1: Mean difference on anthropometric characteristics between male (n=60) and female (n=60) college students

Data were presented as mean ± SD a p-value less than 0.05 is significant

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55

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Percentage (%) in table/ graphs

• We need to calculate measures such as percentages,

cumulative percentages or ratios for accurate and

effective interpretation of data.

• Types of percentage

1. Row percentage

2. Column percentage

3. Total percentage

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Percentage (%) in table/ graphs (cont.)

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RowRow

• Calculated from the total of all the subcategories of one variable that are displayed along a row in different columns, in relation to only one subcategory of the other variable.

ColumnColumn

• Calculated from the total of all the subcategories of one variable that are displayed along a column in different rows, in relation to only one subcategory of the other variable.

TotalTotal

• This standardises the magnitude of each cell; that is, it gives the percentage of respondents who are classified in the subcategories of one variable in relation to the subcategories of the other variable.


Graphs

• A graphic presentation is constructed in relation to two

axes: horizontal (x-axis) and vertical (y-axis).

• If a graph is designed to display only one variable,

represent the subcategories of the variable along the x-

axis and the frequency or count of that subcategory

along the y-axis. The point where the axes intersect is

considered as the zero point for the y-axis.

– When a graph presents two variables, one is displayed on each

axis and the point where they intersect is considered as the

starting or zero point.

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Graphs (cont.)

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Histogram


Graphs (cont.)

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Bar chart


Graphs (cont.)

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Stacked bar chart


Graphs (cont.)

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100% bar chart


Graphs (cont.)

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Box plot


Graphs (cont.)

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Stem-and-leaf display


Graphs (cont.)

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Pie chart


Graphs (cont.)

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Area chart


Graphs (cont.)

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Trend curve


Graphs (cont.)

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Scatter plot


Strategies for communicating research

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Nutritionist/ Nutritionist/ DietitianDietitian

Health care Health care professionalsprofessionals

Policy makersPolicy makers

Health Health consumersconsumers


Audience – Nutritionist & Dietitian

• Oral and visual presentations

– Nutrition/ Dietetics research conferences and meetings

– Collaborative nutritionist/ dietitian groups

– Theses and dissertation defenses

– DVD, videotapes and audio taped presentation

– Websites

• Written reports

– Nutrition/ Dietetics-referred journals, books,

monographs, research newsletters, electronic

databases, foundation reports, theses and dissertation 35


Audience – Health care professionals


– Professional conferences and meetings

– Interdisciplinary collaboration

– DVD and taped presentation

• Written reports

– Professional journals and books

– Newsletters

– Electronic databases

– Foundation reports

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Audience – Policy makers


– Testifying on health problems to state and federal

legislators

• Written reports

– Research reports to legislators

– Research reports to funding agencies


– Official reports and presentations to policy makers,

practitioners and consumers

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Audience – Health consumers


– Television and radio

– Community meetings

– Patient and family teaching

• Written reports

– Newspaper

– News and popular magazines


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Anatomy of an abstract

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IntroductionIntroduction

ObjectiveObjective

MethodsMethods

ResultsResults

ConclusionConclusion


Abstract – Introduction

• Begin simply, usually with no more than a sentence or

two

• Explain why this research is important

• Call this section ‘introduction’, ‘summary’ or

‘background’

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Abstract – Objective

• Report the primary purpose of the study (can be one or

two sentences)

• Call this section ‘objective’, ‘purpose’ or ‘aims’

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Abstract – Methods

• Describe the design of the study, the methods used to

achieve the purpose, and the procedures applied to

control interval validity

• Include the sampling strategy and the analytic plan

• Identify independent and dependent variable

• Do not overload with details

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Abstract – Results

• Summarize the most important results (whether they

were statistically significant or not)

• Keep in mind that a lack of effect may be as the

presence of one

• Report some statistical results here, but limit these to

test statistics and associated p values

• Do not use this section to comment on the meaning of

the results, but simply report them.

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Abstract – Conclusion

• Focus on the most important implication of the findings

and the usefulness for practice

• Address application issues here

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Poster Presentation

• A research report presented as a visual display

• It can be read and viewed by large groups of people

• Informal setting

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Tips for poster presentation

• Use arrows, flowcharts, diagrams, photos to demonstrate the research

• Use bullets in the text

• Use a neutral-color background for the poster

• Self-explanatory graphics should dominate the poster

• Text and graphics should be readable from a distance of 4 to 6 feet.

• Vary the font size according to the importance of the information

• Flow of the poster should be from left to right and top to bottom

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Oral presentation

• An oral presentation is also called as podium

presentation

• Presentation of key elements of a research study at a

professional conference

• Type of presentation expected;

– Informal roundtable discussion ‘OR’

– Highly formalized keynote speeches

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Suggested format for oral presentation

1. An introduction to the problem or clinical issue

2. The purpose or primary aim of the research and the research question

3. Design of the study, including a description of the methods and procedures

4. The findings from the study, including the type of analysis and the major results

5. A discussion of the results, including major limitations, as well as the most important findings for clinical practice

6. Implications for future research and for clinical practice

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Thank YouThank You

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11. processing and displaying data

Health & Medicine