Презентация «Statistical data processing»
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Статистическая обработка данных Prepared by Artur Galimov M. D.
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Methods Section From JAMA (impact factor - 47. 661): In the Methods section, describe statistical methods with enough detail to enable a knowledgeable reader with access to the original data to …
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Study Designs in Medical Research
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Distinguishing Between Study Designs
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Common types of experiments
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Experiment Introduce a treatment to observe its effects Might not involve randomization Might not even have a control group
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Randomized Experiment The gold standard for demonstrating causality Units (people, animals, groups, etc. ) are randomly assigned to receive either treatment or control. If the sample is large enough, …
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Quasi-experiment There is a control group, but no random assignment to treatment vs. control Usually happens because it’s impossible or unethical to do random assignment Assignment to conditions …
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Natural experiment (Not exactly an experiment because the experimenter didn’t manipulate the cause, but the cause occurred) Compare a group that experienced a cause with a group that didn’t (Or …
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Correlational study Nonexperimental because nothing is manipulated Measure some variables and see if there’s a mathematical relationship between them Results can be consistent with causality, but …
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Even randomized experiments aren’t perfect Experimental conditions are usually artificial They’re conducted in one particular time and place – might not generalize to other times or places But we …
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Populations
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Types of Data (Variables) Categorical
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Types of Data (Variables) Categorical
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Histograms Know how to interpret a histogram, i. e. , normal, skewed left (left tail), skewed right (right tail), and most importantly, infer from it the appropriate descriptive statistics and …
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Measures of Central Tendency Mean: what’s commonly called “average” Median (m): middle-most observation of ordered data n odd: m = the (n + 1)/2-th largest observation n even: m = average of the …
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Measures of Variability (Dispersion) Range: difference between largest and smallest observations (or actual values) Interquartile range (IQR): the difference between the 25th and 75th percentiles (or …
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SPSS Output
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SPSS Output
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What is correlation? Correlation captures the extent to which two variables have a linear relationship. Correlation coefficients are descriptive statistics that describe the degree or strength of the …
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SPSS output
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Simple linear regression Purpose: to model the change in one variable (Y, the “dependent variable”) as the other variable (X, the “independent variable”) changes. Assumptions Independence: For any …
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Procedure for linear regression Make a scatterplot of Y vs. X to determine if data are linear and homoscedastic. If the scatterplot looks reasonable, then assume the simple linear regression model: …
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Multilevel Structured Data Multilevel data frequently encountered in social sciences research refer to data which contain multilevel (hierarchical or nested) structure. Multilevel structure indicates …
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Example of Multilevel Data in Prevention Research In school-based substance use prevention research, schools are usually the units of assignment to experimental conditions (program or control). Data …
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Missing Data Data are missing on some variables for some observations. Three goals of missing data handling Minimize bias Maximize use of available information Get good estimates of uncertainty (get …
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Missing Data: Methods to Deal with Missing Listwise Deletion: Delete cases with any missing on the variables being analyzed. Missing replacement by imputation: Mean replacement: using variable mean …
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Methods Section Outline Participants and Procedures Measures Data Analysis
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Participants and Procedures
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Data Analysis
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Q/A Session
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Arthur Galimov e-mail: galimov@usc. edu IG: ar_galimov
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