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A PowerPoint®-based guide to assist in choosing the suitable statistical test. David Normando NOTE: This presentation has the main purpose to assist researchers and students in choosing the appropriate statistical test for studies that examine one variable (Univariate). Some multivariates analyses are also included. Please proceed to the next page ... If you have any suggestion, criticism, please contact the author by e-mail: [email protected] What do you want to do? For an answer, click on the button David Normando 1) I want to assess whether my data have a Normal distribution 2) I want to compare groups (Looking for differences between samples) 3) I want to make correlation or regression analysis between variables. 4) I want to check the replicability of data (analysis of random and systematic error) 5) I would choose the appropriate graph to my data. Tests for Data Analysis Distribution- Normality Normal distribution is requested when using continuos data and n<30 David Normando You may choose the test according to sample size. Use D’Agostino, if n≥10 Use D’Agostino-Pearson, if n≥20 Use Lilliefors or Shapiro-Wilk, for any n value Back to beginning Comparing groups (samples) David Normando What kind of data you have? (Click on the button). Parametric (mean) NUMERICAL Continuous Ex: height / length / weight (Assuming a normal distribution on n>30) How to check Normality ? Ordinal Nonparametric Categorical data Nominal Ex: Middle (1) / Moderate(2) Severe (3) Ex: Frequency: Yes / No Race Gender Back to beginning Numerical Data (parametric) If the distribution is not Normal, skip to "Abnormal" ABNORMAL David Normando How many groups (samples) do you have? 1 2 >2 Numerical Data (parametric) If the distribution is not Normal, skip to "Abnormal" ABNORMAL David Normando Are your samples paired or dependent? No Yes Not sure? Dependent Samples mean: Before X After Left Side X Right Side T1 x T 2 x T3 Numerical Data (parametric) If the distribution is not Normal, skip to "Abnormal" ABNORMAL David Normando Answer: one sample t test Back to beginning Numerical Data (parametric) If the distribution is not Normal, skip to "Abnormal" ABNORMAL David Normando Answer: Independent t test or ANOVA. Back to beginning Numerical Data (parametric) If the distribution is not Normal, skip to "Abnormal" ABNORMAL David Normando Answer: Paired t test or ANOVA for repeated measurements. . Back to beginning Numerical Data (parametric) If the distribution is not Normal, skip to "Abnormal" ABNORMAL David Normando Answer: Analysis of Variance (ANOVA) or MANOVA (Multiple Analysis of Variance), if you have >1 variable. Back to beginning Ordinal Categorical Data (Nonparametric) David Normando How many groups (samples) do you have ? 2 >2 Ordinal Categorical Data (Nonparametric) David Normando Are your samples paired or dependent? No Yes Not sure? Dependent Samples mean: Before X After Left Side X Right Side T1 x T 2 x T3 Ordinal Categorical Data (Nonparametric) David Normando Are your samples paired or dependent? No Yes Not sure? Dependent Samples mean: Before X After Left Side X Right Side T1 x T 2 x T3 Ordinal Categorical Data (Nonparametric) David Normando Answer: Mann-Whitney test Back to beginning Ordinal Categorical Data (Nonparametric) David Normando Answer: Wilcoxon (signed rank test) or Signal test. Back to beginning Ordinal Categorical Data (Nonparametric) David Normando Answer: Kruskal-Wallis’ Test Back to beginning Ordinal Categorical Data (Nonparametric) David Normando Answer: Friedman’s Test Back to beginning Nominal Categorical Data (Nonparametric) David Normando How many groups (samples) do you have ? 2 >2 Nominal Categorical Data (Nonparametric) David Normando Are your samples paired or dependent? No Yes Not sure? Dependent Samples mean: Before X After Left Side X Right Side T1 x T 2 x T3 Nominal Categorical Data (Nonparametric) David Normando Is there any expected value <5 ? No Yes Not sure? If some of the cells in the contingency table give values (expected) lower than 5. Nominal Categorical Data (Nonparametric) David Normando Are your samples paired or dependent? No Yes Not sure? Dependent Samples mean: Before X After Left Side X Right Side T1 x T 2 x T3 Nominal Categorical Data (Nonparametric) David Normando Answer: Chi-square (x²) test or Binomial Test, if using 2 samples and proportion (%) Back to beginning Nominal Categorical Data (Nonparametric) David Normando Answer: Cochran’s test (absolute or relative frequence: %) Back to beginning Nominal Categorical Data (Nonparametric) David Normando Answer: McNemar’s test Back to beginning Nominal Categorical Data (Nonparametric) David Normando Answer: Exact Fisher’s test Back to beginning Correlation or Regression Analysis David Normando What kind of data you have? (Click on the button). Parametric (mean) Numerical Ex: height / length / weight (Assuming a normal distribution) How to check Normality ? Ordinals Ex: Middle (1) / Moderate(2) Severe (3) Nominal Ex: Frequency: Yes / No Race Gender Nonparametric Categorical data Numerical Data (parametric) If the distribution is not Normal, skip to "Abnormal" ABNORMAL David Normando How many variables do you have? 2 >2 Correlation tests or regression analysis to Continuos data If the distribution is not Normal, skip to "Abnormal" ABNORMAL David Normando Answer: Pearson’s Correlation Simple Linear Regression Back to beginning Correlation tests or regression analysis to Continuos data If the distribution is not Normal, skip to "Abnormal" ABNORMAL David Normando Answer: Pearson’s Correlation (parcial) or Canonical Correlation Multiple Linear Regression NOTE: For Correlation all variables examined must have a Normal Distribution. For Linear Regression dependent variable must have a Normal Distribution How to check Normality ? Back to beginning Correlation test to Ordinal data (nonparametric) David Normando Answer : Spearman or Kendal Correlation Back to beginning Correlation and Regression Analysis to Nominal data (nonparametric) David Normando How many variables do you have? 2 >2 Correlation test to Nominal data (nonparametric) David Normando Answer: Contingency coefficient C Simple Logistic Regression Back to beginning Correlation test to Nominal data (nonparametric) David Normando Answer: Contingency coefficient C Multiple Logistic Regression Back to beginning Replicability or Reproducibility (Systematic error) David Normando What kind of data you have? (Click on the button). Parametric (mean) Numerical Ex: height / length / weight (Assuming a normal distribution) How to check Normality ? Ordinal Nonparametric Categorical data Nominal Ex: Middle (1) / Moderate(2) Severe (3) Ex: Frequency: Yes / No Race Gender Replicability or Reproducibility (Systematic error for numerical data) ABNORMAL David Normando Answer: Parametric test for dependent data 2 samples >2 samples Note: Intraclass correlation can be used, if you would like to check the association between 2 or more measurements. For random or casual error , you may use TEM (technical error measurement): D= difference between repeated measures n=number of individuals Back to beginning Replicability or Reproducibility (Systematic error for ordinal data) David Normando Answer: Weighted Kappa NOTE: in case of an ordinal variable, nonparametric tests for paired or dependent data can also be used 2 sample > 2 samples Back to beginning Replicability or Reproducibility (Systematic error for Nominal data) David Normando Answer: Kappa Back to beginning Graph Selection David Normando What kind of data you have? (Click on the button). Parametric (mean) Nonparametric Categorical data Numerical Ordinal Nominal Ex: height / length / weight (Assuming a normal distribution) Ex: Middle (1) / Moderate(2) Severe (3) Ex: Frequency: Yes / No Race Gender Back to beginning Graph Selection David Normando Comparing Independent Samples Comparing Dependent Samples (paired) Making Data Correlation or regression Not sure? Dependent Samples mean: Before X After Left Side X Right Side T1 x T 2 x T3 BOX-PLOT - Comparing Groups. Continuous or Ordinal Data (Score) David Normando This chart describes the measure of central tendency (MEAN for continuos data or MEDIAN for Ordinal data), measures of dispersion (Standard deviation for parametric data or interquartiles deviation for Ordinal data) and the whiskers (maximum and minimum values ) Outlier: an observation that is numerically distant from the rest of the data. Back Line graph for longitudinal data David Normando This chart describes the measure of central tendency (mean for Continuos data or median for Ordinal data) longitudinally Back Graphic for Correlation Tests or Regression Analysis David Normando Back Bar/Column Graphic Nominal data (frequency) David Normando Back