1 SPSS 201: Using SPSS to Perform Commonly Used Statistical Testing in Medical Research (Workshop)...

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SPSS 201: Using SPSS to SPSS 201: Using SPSS to Perform Commonly Used Perform Commonly Used

Statistical Testing in Medical Statistical Testing in Medical Research (Workshop) Research (Workshop)

Dr. Daisy DaiDr. Daisy Dai

Department of Medical Department of Medical ResearchResearch

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Who are biostatisticians?Who are biostatisticians?

Ashley ShermanAshley Sherman

Phone: 816-701-1347Phone: 816-701-1347 [email protected]@cmh.edu

Daisy DaiDaisy Dai

Phone: 816-701-5233Phone: 816-701-5233 Email: Email: [email protected]@cmh.edu

ConsultationConsultation Experimental design Experimental design

and sampling planand sampling plan Collaboration in Collaboration in

presentation and presentation and publication of publication of studiesstudies

EducationEducation ResearchResearch

mailto:[email protected]

mailto:[email protected]

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Statistical Courses Statistical Courses

SPSS 201: Using SPSS to SPSS 201: Using SPSS to perform statistical tests Iperform statistical tests I

SPSS 202: Using SPSS to SPSS 202: Using SPSS to perform statistical tests IIperform statistical tests II

SPSS 204: Using SPSS to SPSS 204: Using SPSS to manage datamanage data

SPSS 203: Summarize data SPSS 203: Summarize data with tables and graphswith tables and graphs

STA 101: Properly Setting STA 101: Properly Setting up and Designing a Clinical up and Designing a Clinical Research Study Including Research Study Including Power Analysis for Proper Power Analysis for Proper Patient Numbers (July 16Patient Numbers (July 16thth))

STA 102: Commonly Used STA 102: Commonly Used

Statistical Tests in Medical Statistical Tests in Medical Research - Part IResearch - Part I

STA 103: Commonly Used STA 103: Commonly Used Statistical Tests in Medical Statistical Tests in Medical Research - Part IIResearch - Part II

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ContentsContents

Review statistical tools (1 hour)Review statistical tools (1 hour) Introduce SPSS (30 minutes)Introduce SPSS (30 minutes) Practice (1 hour)Practice (1 hour) Questions and discussions ( 30 Questions and discussions ( 30

minutes) minutes)

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Statistical toolsStatistical tools

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Medical ResearchMedical Research

Clinical TrialsClinical Trials Intervention or therapeuticIntervention or therapeutic PreventativePreventative

Retrospective StudiesRetrospective Studies

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DataData

Medical dataMedical data Physics dataPhysics data Chemistry dataChemistry data EducationEducation EconomicsEconomics Social studiesSocial studies SensorySensory NutritionNutrition Many more… Many more…

Continuous variableContinuous variable Interval variableInterval variable Ordinal variableOrdinal variable

Categorical variableCategorical variable Binary variableBinary variable Discrete variableDiscrete variable Ordinal variableOrdinal variable

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Information CollectionsInformation Collections

1.1. Historical DataHistorical Data Pro:Pro: Convenient; Save a lot of work Convenient; Save a lot of work Con:Con: Outdated; Different Objectives and Designs; Unknown Outdated; Different Objectives and Designs; Unknown

Detailed InformationDetailed Information

2.2. CensusCensus Pro:Pro: reliable, accurate and comprehensive (e.g. Population reliable, accurate and comprehensive (e.g. Population

census)census) Con:Con: Time consuming; requiring more resources; difficult to Time consuming; requiring more resources; difficult to

investigate all subjects in the populationinvestigate all subjects in the population

3.3. SamplingSampling Pro:Pro: Efficient; Less risky; exploratory; informative Efficient; Less risky; exploratory; informative Caveats: Selection bias; misinterpretation; design flawCaveats: Selection bias; misinterpretation; design flaw

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StatisticsStatistics

Descriptive StatisticsDescriptive Statistics Methods to organize and summarize informationMethods to organize and summarize information Mean, median, max, min, frequency and Mean, median, max, min, frequency and

proportions, etc. that summarize sample proportions, etc. that summarize sample demographicsdemographics

Inferential StatisticsInferential Statistics Methods to draw conclusions about a population Methods to draw conclusions about a population

based on information obtained from a sample of based on information obtained from a sample of the populationthe population

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Population

Sample

Descriptive Statistics

Inferential Statistics

Sampling Plan

Conclusion

1111

Summary StatisticsSummary Statistics

Measures of CenterMeasures of Center MeanMean

Median: the middle Median: the middle value in its ordered list value in its ordered list

Mode: the most Mode: the most frequently occurring frequently occurring value value

Measures of variationMeasures of variation Range: the difference Range: the difference

between the largest and between the largest and smallest value in the smallest value in the data set, i.e., data set, i.e., Range=Max-Min.Range=Max-Min.

Standard deviation: Standard deviation: measure variation by measure variation by indicating how far, on indicating how far, on average, the average, the observations are from observations are from the mean. the mean.

n

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ii

1

2

2 2 1

1 1

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1 1

n

in ni

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We will talk more about data

summary and distribution graphs in SPSS 204 Workshop.

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Exercise: Determine for the mean, median and Exercise: Determine for the mean, median and mode, which measure of center is most appropriate mode, which measure of center is most appropriate

in the following case studies?in the following case studies?

A student takes four exams in a biology A student takes four exams in a biology class. His grades are 88, 75, 95, and 100. class. His grades are 88, 75, 95, and 100.

The National Association of REALTORS The National Association of REALTORS publishes data on resale prices of U.S. publishes data on resale prices of U.S. homes. homes.

In the 2003 Boston Marathon, there were In the 2003 Boston Marathon, there were two categories of official finishers: male two categories of official finishers: male and female, of which there were 10,737 and female, of which there were 10,737 and 6,309, respectively.and 6,309, respectively.

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Statistical Testing Statistical Testing ProceduresProcedures

1.1. Clarify study Clarify study objectives. objectives.

2.2. Establish Establish hypotheses. hypotheses.

3.3. Determine the Determine the outcome variables, outcome variables, treatment groups, treatment groups, risk factors and risk factors and covariates. covariates.

4.4. Perform appropriate Perform appropriate statistical testing.statistical testing.

5.5. Interpret results. Interpret results.

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Statistical Testing Statistical Testing ProceduresProcedures

1.1. Null HypothesisNull Hypothesis

- Ho: Mean_Treatment=Mean_ControlHo: Mean_Treatment=Mean_Control

2.2. Alternative HypothesisAlternative Hypothesis

- Ha: Mean_Treatment Ha: Mean_Treatment ≠≠ Mean_Control (Two-sided Test) Mean_Control (Two-sided Test)- Ha: Mean_Treatment > Mean_Control (One-sided Test)Ha: Mean_Treatment > Mean_Control (One-sided Test)- Ha: Mean_Treatment < Mean_Control (One-sided Test)Ha: Mean_Treatment < Mean_Control (One-sided Test)

3.3. Calculate statisticsCalculate statistics

4.4. Make InferenceMake Inference

- If P-value > 0.05, then Ho holdsIf P-value > 0.05, then Ho holds- If P-value < 0.05, then Ha holdsIf P-value < 0.05, then Ha holds

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Continuous VariablesContinuous Variables

Two or multiple treatment Two or multiple treatment groupsgroups

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Two samples t-testTwo samples t-test

Compare the means of a normally Compare the means of a normally distributed interval dependent variable distributed interval dependent variable for two independent groups. for two independent groups.

1,2/0

21

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Case Study: FEVCase Study: FEV1 1 ChangesChanges

A new compound, ABC-A new compound, ABC-123, is being developed 123, is being developed for long-term treatment for long-term treatment of patients with chronic of patients with chronic asthma. Asthma patients asthma. Asthma patients were enrolled in a were enrolled in a double-blind study and double-blind study and randomized to receive randomized to receive daily oral or a placebo daily oral or a placebo

for 6 weeks.for 6 weeks.

FEV1 after 6-week treatment

Placebo Test

asthmatic patients

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FEVFEV1 1 DataData

Test GroupTest Group

Patient IDPatient ID BaselineBaseline week 6week 6

101101 1.351.35 n/an/a

103103 3.223.22 3.553.55

106106 2.782.78 3.153.15

108108 2.452.45 2.32.3

109109 1.841.84 2.372.37

110110 2.812.81 3.23.2

113113 1.91.9 2.652.65

116116 33 3.963.96

118118 2.252.25 2.972.97

120120 2.862.86 2.282.28

121121 1.561.56 2.672.67

124124 2.662.66 3.763.76

Placebo GroupPlacebo Group


102102 3.013.01 3.93.9

104104 2.242.24 3.013.01

105105 2.252.25 2.472.47

107107 1.651.65 1.991.99

1111 1.951.95 n/an/a

112112 3.053.05 3.263.26

114114 2.52.5 2.552.55

115115 1.61.6 2.22.2

117117 .77.77 2.562.56

119119 2.062.06 2.92.9

122122 1.711.71 n/an/a

123123 3.543.54 2.922.92

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P-value P-value

What is the difference

between std and std error?

2020

Mean and Error BarMean and Error Bar

Conclusion:Conclusion:

As compared to As compared to placebo, the new placebo, the new drug did not show drug did not show any effect on FEVany effect on FEV11. .

2121

Paired t-testPaired t-test

Compare the means Compare the means of a normally of a normally distributed interval distributed interval dependent variable dependent variable for two related for two related groups.groups.



101101 1.351.35 n/an/a

103103 3.223.22 3.553.55

106106 2.782.78 3.153.15

108108 2.452.45 2.32.3

109109 1.841.84 2.372.37

110110 2.812.81 3.23.2

113113 1.91.9 2.652.65

116116 33 3.963.96

118118 2.252.25 2.972.97

120120 2.862.86 2.282.28

121121 1.561.56 2.672.67

124124 2.662.66 3.763.76

2222

P-value

Conclusion: For subjects on the new drug,

FEV1 at week 6 is significantly higher than

baseline.

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One-way ANOVAOne-way ANOVA

Test for differences of the means for Test for differences of the means for continuous variables in multiple continuous variables in multiple independent treatment groups.independent treatment groups.

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2424

Case Study: HAM-A Scores in Case Study: HAM-A Scores in GADGAD

HAM-A Score after 10-week treatment

Placebo 100 mg SN-X95

Patients with GAD

25mg SN-X95

A new serotonin-update inhibiting A new serotonin-update inhibiting agent, SN-X95, is being studied in agent, SN-X95, is being studied in subjects with general anxiety subjects with general anxiety disorder (GAD). Fifty-two subjects disorder (GAD). Fifty-two subjects diagnosed with GAD were enrolled diagnosed with GAD were enrolled and randomly assigned to one of and randomly assigned to one of three treatment groups: three three treatment groups: three treatment groups: 25mg SN-X95, treatment groups: 25mg SN-X95, 100mg SN-X95 or placebo. After 10 100mg SN-X95 or placebo. After 10 weeks of once-daily oral dosing in a weeks of once-daily oral dosing in a double-blind fashion, a test based on double-blind fashion, a test based on the Hamilton Rating Scale for the Hamilton Rating Scale for Anxiety (HAM-A) was administered. Anxiety (HAM-A) was administered. This test consists of 14 anxiety-This test consists of 14 anxiety-related items (e.g. ‘anxious mood’, related items (e.g. ‘anxious mood’, ‘tension’, ‘insomnia’, ‘fear’, etc.), ‘tension’, ‘insomnia’, ‘fear’, etc.), each rated by the subject as ‘no each rated by the subject as ‘no present’, ‘mild’, ‘moderate’, ‘severe’, present’, ‘mild’, ‘moderate’, ‘severe’, or ‘very severe’. HAM-A test scores or ‘very severe’. HAM-A test scores were founded by summing the coded were founded by summing the coded values of all 14 items using the values of all 14 items using the numeric coding scheme of 0 for “not numeric coding scheme of 0 for “not present”, 1 for …. Are there any present”, 1 for …. Are there any differences in means HAM-A test differences in means HAM-A test score among the three groups?score among the three groups?

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DataDataLo-DoseLo-Dose Hi-DoseHi-Dose PlaceboPlacebo

2121 1616 2222

1818 2121 2626

1919 3131 2929

9999 2525 1919

2828 2323 9999

2222 2525 3333

3030 1818 3737

2727 2020 2525

2828 1818 2828

1919 1616 2626

2323 2424 9999

2222 2222 3131

2020 2121 2727

1919 1616 3030

2626 3333 2525

3535 2121 2222

9999 1717 3636

2626

P-value

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Mean and Error BarMean and Error Bar

Conclusion:Conclusion:

There is significant There is significant difference in mean difference in mean HAM-A among HAM-A among three treatment at three treatment at 95% confidence 95% confidence level. level.

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Categorical Variables Categorical Variables

Two or multiple treatment Two or multiple treatment groupsgroups

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Fisher’s Exact TestFisher’s Exact Test

A conservative non-parametric test A conservative non-parametric test about a relationship between two about a relationship between two categorical variables. categorical variables.

RespondersResponders Non-respondersNon-responders TotalTotal

Group 1Group 1 NN1111 NN1212 NN1111+N+N1212

Group 2Group 2 NN2211 NN2222 NN2211+N+N2222

CombinedCombined NN1111+N+N2211 NN1212+ N+ N2222 N N

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Case Study: CHF Incidence Case Study: CHF Incidence in CABG after ARAin CABG after ARA

A new adenosine-releasing agent (ARA), A new adenosine-releasing agent (ARA), thought to reduce side effects in patients thought to reduce side effects in patients undergoing coronary artery bypass surgery undergoing coronary artery bypass surgery (CABG), was studied in a pilot trial. (CABG), was studied in a pilot trial.

CHFCHF No CHFNo CHF TotalTotal

ARAARA 2 (6%)2 (6%) 3333 3535

PlaceboPlacebo 5 (25%)5 (25%) 2020 2525

CombinedCombined 77 5353 6060

Fisher’s exact test: p=0.0455

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Chi-square testChi-square test

Test a relationship between two Test a relationship between two categorical variables. The chi-square categorical variables. The chi-square test assumes that the expected test assumes that the expected value for each cell is five or higher. value for each cell is five or higher.

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Case Study: ADR Frequency Case Study: ADR Frequency with Antibiotic Treatmentwith Antibiotic Treatment

A study was conducted to monitor A study was conducted to monitor the incidence of GI adverse drug the incidence of GI adverse drug reactions of a new antibiotic used in reactions of a new antibiotic used in lower respiratory tract infections. lower respiratory tract infections.

RespondersResponders Non-respondersNon-responders TotalTotal

Test Test (new antibiotic)(new antibiotic) 22 (33%)22 (33%) 4444 6666

ControlControl(erythromycin)(erythromycin) 28 (54%)28 (54%) 2424 5353

CombinedCombined 50 (42%)50 (42%) 6868 118118

Chi-square test: p=0.0252; Fisher’s exact test: p=0.0385

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Other testsOther tests

One-way repeated One-way repeated measures ANOVAmeasures ANOVA

Repeated measures Repeated measures logistic regressionlogistic regression

Factorial ANOVAFactorial ANOVA Friedman testFriedman test Factorial logistic Factorial logistic

regressionregression Simple Linear Simple Linear

RegressionRegression Multiple RegressionMultiple Regression

Factor analysisFactor analysis Multiple logistic Multiple logistic

regressionregression Discriminant analysis Discriminant analysis One-way MANOVAOne-way MANOVA Multivariate multiple Multivariate multiple

regressionregression Canonical correlationCanonical correlation Analysis of covarianceAnalysis of covariance

We will cover all tests including non-parametric tests in SPSS 202 Workshop.

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Questions?Questions?

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Introduction to SPSSIntroduction to SPSS

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What is SPSS?What is SPSS?

Statistical software. Statistical software. 16 server licenses. 16 server licenses. SPSS 18. SPSS 18.

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SPSS Data EntrySPSS Data Entry

SPSS data can be entered manually. SPSS data can be entered manually. The format is ready for analysis.The format is ready for analysis.

SAS, Excel, txt, etc. data can be SAS, Excel, txt, etc. data can be easily imported to SPSS. easily imported to SPSS.

SPSS data files are saved as “SPSS SPSS data files are saved as “SPSS data document (.sav)”. data document (.sav)”.

SPSS output files are saved as “SPSS SPSS output files are saved as “SPSS viewer document (.spv)”. viewer document (.spv)”.

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SPSS Data EntrySPSS Data Entry

SPSS has a few unique features in data entry. SPSS has a few unique features in data entry. Categorical variables need to be coded. For instance, Categorical variables need to be coded. For instance,

code male as 1 and female as 0 or vice versa.code male as 1 and female as 0 or vice versa. When you have two treatments, test and control, please When you have two treatments, test and control, please

use 1 for test and 0 for control. use 1 for test and 0 for control. Categorical variables that are not coded in other Categorical variables that are not coded in other

sourced data files will not be imported or analyzed sourced data files will not be imported or analyzed

properly in SPSS. properly in SPSS. Continuous variables don’t need coding. Continuous variables don’t need coding. Missing values needs to be defined in “variable view” Missing values needs to be defined in “variable view”

page. page.

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Example: CDC Survey DataExample: CDC Survey Data

An allergy survey was conducted in An allergy survey was conducted in 2005 and 2006 to children more than 2005 and 2006 to children more than 1 year old. 1 year old.

Two data sets, allergy questionnaire Two data sets, allergy questionnaire and demographic information, are and demographic information, are saved in sas export format. saved in sas export format.

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TasksTasks

Import these two SAS data files to Import these two SAS data files to SPSS and save them as SPSS data SPSS and save them as SPSS data file. file.

Sort each data set by study ID.Sort each data set by study ID. Merge allergy variables and Merge allergy variables and

demographic variables.demographic variables. Save new data set as SPSS data file. Save new data set as SPSS data file.

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Log in SPSS Log in SPSS

CMH offers server CMH offers server version SPSS 18. Any version SPSS 18. Any employee can log in employee can log in SPSS from your SPSS from your employee account.employee account.

Go to Go to Start Start

->Program->Program

->Accessories->Accessories

-> Remote -> Remote Desktop Desktop ConnectionConnection

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In the prompted In the prompted connection connection window, enter window, enter cmhterm. cmhterm.

ClickClick Connect. Connect.

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In the Log On In the Log On Window, enter your Window, enter your cmh user namecmh user name and and passwordpassword. .

Choose log on to Choose log on to CMHCMH

ClickClick OK. OK.

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Task 1: Import Data Task 1: Import Data

We need to import two data sets to SPSS.We need to import two data sets to SPSS. Allergy qustionaire: Allergy qustionaire: aqq_d.xptaqq_d.xpt (xpt is sas export (xpt is sas export

file)file) Demographic information: Demographic information: demo_d.xptdemo_d.xpt

Please note that SPSS is on server and data Please note that SPSS is on server and data must be saved in shared drive such as must be saved in shared drive such as u u drive or w drivedrive or w drive. You will not be able to find . You will not be able to find the file in SPSS if you save them on your local the file in SPSS if you save them on your local disk.disk.

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Double click spss Double click spss 18 icon on the 18 icon on the screen. screen.

In the task wizard, In the task wizard, click click Open an Open an existing sourceexisting source..

Click Click OKOK..

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Just in case wizard Just in case wizard does not prompt, does not prompt, you can go to you can go to filefile

-> -> OpenOpen

-> -> DataData

4747


Select Select the folderthe folder. . Choose Choose agg_d fileagg_d file.. Select Select xpt formatxpt format.. Click Click OpenOpen..

Note: SPSS is Note: SPSS is compatible with other compatible with other commonly used commonly used statistical and data statistical and data management software management software packages. Excel, SAS, packages. Excel, SAS, Access files are all Access files are all convertible to SPSS. convertible to SPSS.

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Now the data is Now the data is open. open.

You can see the You can see the data in “data in “data Viewdata View” ” tab.tab.

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The data structure, The data structure, variable name, variable name, label, etc. are in label, etc. are in ““Variable ViewVariable View” ” tab. tab.

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Task 2: Sort Data Task 2: Sort Data

Variable to be sort: Variable to be sort: SEQNSEQN, that is, , that is, Respondent sequence number. Respondent sequence number.

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Task 2: Sort Data Task 2: Sort Data

Go to Go to DataData and select and select Sort CasesSort Cases..

On On Sort Cases pageSort Cases page, , select the variable, select the variable, Respondent sequence Respondent sequence numbernumber..

Click on Click on right arrowright arrow.. Choose Choose AscendingAscending or or

DescendingDescending.. Click Click OKOK. .

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PracticePractice

Now let’s repeat this process by Now let’s repeat this process by doing the following:doing the following: Open the demographic data, Open the demographic data,

demo_d.xptdemo_d.xpt.. Sort the data by variable, Sort the data by variable, Respondent Respondent

Sequence NumberSequence Number. .

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Task 3: Merge Two Data Task 3: Merge Two Data SetsSets

Two data sets need to be linked by Two data sets need to be linked by key variables.key variables.

In our case, the key variable is In our case, the key variable is SEQN-SEQN-Respondent Sequence NumberRespondent Sequence Number..

Make sure the key variable has the Make sure the key variable has the same name and variable type in two same name and variable type in two data sets. data sets.

Both data sets needs to be sorted by Both data sets needs to be sorted by the key variable. the key variable.

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Under any data Under any data set, go to set, go to DataData

-> -> Merge FileMerge File

-> -> Add VariablesAdd Variables

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Choose the other Choose the other data to add on. data to add on.

Note, this page will Note, this page will look different in look different in SPSS 18. By all SPSS 18. By all means, choose the means, choose the other data set. other data set.

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Task 4: Save the New DataTask 4: Save the New Data

Go to Go to FileFile

-> -> Save As…Save As… Select Select the folderthe folder.. Create new file, Create new file,

MergedDataMergedData.. Choose Choose SPSS data SPSS data

formatformat. . Click Click SaveSave..

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Task 4: Save the New DataTask 4: Save the New Data

Go to Go to DataData

-> -> Merge FileMerge File

-> -> Add VariablesAdd Variables

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We will cover more We will cover more data management in data management in SPSS 203 workshop. SPSS 203 workshop.

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Let’s play with SPSSLet’s play with SPSS

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Project 1: FEVProject 1: FEV1 1 ChangesChanges

6161

Case Study: FEVCase Study: FEV1 1 ChangesChanges

A new compound, ABC-A new compound, ABC-123, is being developed 123, is being developed for long-term treatment for long-term treatment of patients with chronic of patients with chronic asthma. Asthma patients asthma. Asthma patients were enrolled in a were enrolled in a double-blind study and double-blind study and randomized to receive randomized to receive daily oral or a placebo daily oral or a placebo

for 6 weeks.for 6 weeks.

FEV1 after 6-week treatment

Placebo Test

asthmatic patients

6262

FEVFEV1 1 DataData



101101 1.351.35 n/an/a

103103 3.223.22 3.553.55

106106 2.782.78 3.153.15

108108 2.452.45 2.32.3

109109 1.841.84 2.372.37

110110 2.812.81 3.23.2

113113 1.91.9 2.652.65

116116 33 3.963.96

118118 2.252.25 2.972.97

120120 2.862.86 2.282.28

121121 1.561.56 2.672.67

124124 2.662.66 3.763.76

Placebo GroupPlacebo Group


102102 3.013.01 3.93.9

104104 2.242.24 3.013.01

105105 2.252.25 2.472.47

107107 1.651.65 1.991.99

1111 1.951.95 n/an/a

112112 3.053.05 3.263.26

114114 2.52.5 2.552.55

115115 1.61.6 2.22.2

117117 .77.77 2.562.56

119119 2.062.06 2.92.9

122122 1.711.71 n/an/a

123123 3.543.54 2.922.92

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TasksTasks

1.1. Log in to intranet and open SPSS.Log in to intranet and open SPSS.

2.2. Define variables and missing values in “variable Define variables and missing values in “variable

view” tab. view” tab.

3.3. Enter data in “data view” tab. Enter data in “data view” tab.

4.4. Perform two-sample t-tests to compare FEV1 at Perform two-sample t-tests to compare FEV1 at

6 weeks between test and control. 6 weeks between test and control.

5.5. Generate mean and error bar graph for two Generate mean and error bar graph for two

groups. groups.

6.6. Interpret the SPSS output and make conclusion.Interpret the SPSS output and make conclusion.

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Tasks to be continuedTasks to be continued

7.7. Perform paired t-test to compare the FEV Perform paired t-test to compare the FEV between baseline and 6 weeks for test between baseline and 6 weeks for test group. group.

8.8. Interpret SPSS results and draw conclusions.Interpret SPSS results and draw conclusions.

9.9. Save SPSS data and SPSS output Save SPSS data and SPSS output respectively. respectively.

10.10. Open SPSS data and SPSS output by double Open SPSS data and SPSS output by double clicking the icons. clicking the icons.

11.11. Close both files. Close both files.

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Project 2: Project 2: HAM-A Scores in HAM-A Scores in GADGAD

6666

Case Study: HAM-A Scores in Case Study: HAM-A Scores in GADGAD

HAM-A Score after 10-week treatment

Placebo 100 mg SN-X95

Patients with GAD

25mg SN-X95

A new serotonin-update inhibiting A new serotonin-update inhibiting agent, SN-X95, is being studied in agent, SN-X95, is being studied in subjects with general anxiety subjects with general anxiety disorder (GAD). Fifty-two subjects disorder (GAD). Fifty-two subjects diagnosed with GAD were enrolled diagnosed with GAD were enrolled and randomly assigned to one of and randomly assigned to one of three treatment groups: three three treatment groups: three treatment groups: 25mg SN-X95, treatment groups: 25mg SN-X95, 100mg SN-X95 or placebo. After 10 100mg SN-X95 or placebo. After 10 weeks of once-daily oral dosing in a weeks of once-daily oral dosing in a double-blind fashion, a test based on double-blind fashion, a test based on the Hamilton Rating Scale for the Hamilton Rating Scale for Anxiety (HAM-A) was administered. Anxiety (HAM-A) was administered. This test consists of 14 anxiety-This test consists of 14 anxiety-related items (e.g. ‘anxious mood’, related items (e.g. ‘anxious mood’, ‘tension’, ‘insomnia’, ‘fear’, etc.), ‘tension’, ‘insomnia’, ‘fear’, etc.), each rated by the subject as ‘no each rated by the subject as ‘no present’, ‘mild’, ‘moderate’, ‘severe’, present’, ‘mild’, ‘moderate’, ‘severe’, or ‘very severe’. HAM-A test scores or ‘very severe’. HAM-A test scores were founded by summing the coded were founded by summing the coded values of all 14 items using the values of all 14 items using the numeric coding scheme of 0 for “not numeric coding scheme of 0 for “not present”, 1 for …. Are there any present”, 1 for …. Are there any differenceds in means HAM-A test differenceds in means HAM-A test score among the three groups?score among the three groups?

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DataDataLo-DoseLo-Dose Hi-DoseHi-Dose PlaceboPlacebo

2121 1616 2222

1818 2121 2626

1919 3131 2929

9999 2525 1919

2828 2323 9999

2222 2525 3333

3030 1818 3737

2727 2020 2525

2828 1818 2828

1919 1616 2626

2323 2424 9999

2222 2222 3131

2020 2121 2727

1919 1616 3030

2626 3333 2525

3535 2121 2222

9999 1717 3636

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TasksTasks

1.1. Open data in excel. Make sure the data structure, Open data in excel. Make sure the data structure,

variables and missing values are set up properly. variables and missing values are set up properly.

2.2. Import Excel to SPSS.Import Excel to SPSS.

3.3. Perform one-way ANOVA to compare high dose, low dose Perform one-way ANOVA to compare high dose, low dose

and control groups.and control groups.

4.4. Generate mean and error bar graph for three groups.Generate mean and error bar graph for three groups.

5.5. If the global F-test is significant, then perform post-hoc If the global F-test is significant, then perform post-hoc

pair-wise comparisons. pair-wise comparisons.

6.6. Interpret the SPSS output and make conclusion.Interpret the SPSS output and make conclusion. 7.7. Save data and output. Save data and output.

8.8. Close files. Close files.

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Project 3: CHF Incidence in Project 3: CHF Incidence in CABG after ARACABG after ARA

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Case study: CHF Incidence in Case study: CHF Incidence in CABG after ARACABG after ARA

A new adenosine-releasing agent (ARA), thought A new adenosine-releasing agent (ARA), thought to reduce side effects in patients undergoing to reduce side effects in patients undergoing coronary artery bypass surgery (CABG), was coronary artery bypass surgery (CABG), was studied in a pilot trial That enrolled 35 patients studied in a pilot trial That enrolled 35 patients who receive active medication and 20 patients who receive active medication and 20 patients who received a placebo. Follow-up observation who received a placebo. Follow-up observation revealed that 2 patients who received active revealed that 2 patients who received active medication and 5 patients who received the medication and 5 patients who received the placebo had shown symptoms of congestive heart placebo had shown symptoms of congestive heart failure (CHF) within 90 days post surgery. Is this failure (CHF) within 90 days post surgery. Is this evidence of a reduced rate of CHF for patients evidence of a reduced rate of CHF for patients treated with the ARA compound?treated with the ARA compound?

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TasksTasks

1.1. Open SPSS data. Open SPSS data.

2.2. Summarize frequency, percentage in two-way Summarize frequency, percentage in two-way

contingency table.contingency table.

3.3. Perform Fisher’s exact test. Perform Fisher’s exact test.

4.4. Perform Chi-square test.Perform Chi-square test.

5.5. Compare Fisher’s exact test with Chi-square Compare Fisher’s exact test with Chi-square

test. test.

6.6. Interpret the SPSS output and make conclusion.Interpret the SPSS output and make conclusion. 7.7. Close files. Close files.

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Project 4: ADR Frequency Project 4: ADR Frequency with Antibiotic Treatmentwith Antibiotic Treatment

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Case Study: ADR Frequency Case Study: ADR Frequency with Antibiotic Treatmentwith Antibiotic Treatment

A study was conducted to monitor the A study was conducted to monitor the incidence of GI adverse drug reactions incidence of GI adverse drug reactions of a new antibiotic used in lower of a new antibiotic used in lower respiratory tract infections. Two parallel respiratory tract infections. Two parallel groups were included in the study. One groups were included in the study. One group consisted of 66 LRTI patients group consisted of 66 LRTI patients randomized to receive the new randomized to receive the new treatment and a reference group of 52 treatment and a reference group of 52 patients randomized to receive patients randomized to receive erythromycin. erythromycin.

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TasksTasks

1.1. Open SPSS data. Open SPSS data.

2.2. Summarize frequency, percentage in two-way Summarize frequency, percentage in two-way

contingency table.contingency table.

3.3. Perform Fisher’s exact test. Perform Fisher’s exact test.

4.4. Perform Chi-square test.Perform Chi-square test.

5.5. Compare Fisher’s exact test with Chi-square Compare Fisher’s exact test with Chi-square

test. test.

6.6. Interpret the SPSS output and make conclusion.Interpret the SPSS output and make conclusion. 7.7. Close files. Close files.

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Let us know statistics Let us know statistics topics you are topics you are interested. interested.

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In summary…In summary…

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Thank YouThank You

For more information, visit my websiteFor more information, visit my website

http://www.childrensmercy.org/contenthttp://www.childrensmercy.org/content/view.aspx?id=9740/view.aspx?id=9740

Or go to Scope ->Research -> Medical Or go to Scope ->Research -> Medical Research -> StatisticsResearch -> Statistics

http://www.childrensmercy.org/content/view.aspx?id=9740

http://www.childrensmercy.org/content/view.aspx?id=9740

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ReferencesReferences

Medical Statistics by Campbell et al.Medical Statistics by Campbell et al. Introductory Statistics by Neil WeissIntroductory Statistics by Neil Weiss Common Statistical Methods for Common Statistical Methods for

Clinical Research by WalkerClinical Research by Walker

1 SPSS 201: Using SPSS to Perform Commonly Used Statistical Testing in Medical Research (Workshop)...

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Transcript of 1 SPSS 201: Using SPSS to Perform Commonly Used Statistical Testing in Medical Research (Workshop)...