Biostatistic : Biostatistic Dr.Abdelazim Hussein Khalafalla Frequency data ( counting) : Frequency data ( counting) In any type of study either you want to test association or differences between 2 variables( not group) e.g ca lung and smoking
Chi-square test (unpaired,unmatched,independent sample)
McNamer test (paired,matched,dependent sample) Student test (pooled) : Student test (pooled) The Independent-Samples T Test procedure compares means for two groups of cases.
Ideally, for this test, the subjects should be randomly assigned to two groups, so that any difference in response is due to the treatment (or lack of treatment) and not to other factors. Entering data for student test : Entering data for student test Compare
(1) and non
vari (2) Student test (pooled) : Student test (pooled) A low significance value for the t test (typically less than 0.05) indicates that there is a significant difference between the two group means.
If the confidence interval for the mean difference does not contain zero, this also indicates that the difference is significant
If the significance value is high and the confidence interval for the mean difference contains zero, then you cannot conclude that there is a significant difference between the two group means. Student’s test : Student’s test Example.
Patients with high blood pressure are randomly assigned to a placebo group and a treatment group.
The placebo subjects receive an inactive pill and the treatment subjects receive a new drug that is expected to lower blood pressure.
After treating the subjects for two months, the two-sample t test is used to compare the average blood pressures for the placebo group and the treatment group.
Each patient is measured once and belongs to one group. Interpretation of the output of student’s test : Interpretation of the output of student’s test The Independent-Samples T Test procedure compares means for two groups of cases
If the significance value for the Levene test is high (typically greater that 0.05)... Use the results that assume equal variances for both groups.
If the significance value for the Levene test is low... Use the results that do no assume equal variances for both groups. Paired sample T test(depedent) : Paired sample T test(depedent) The Paired-Samples T Test procedure compares the means of two variables for a single group.
Example. In a study on high blood pressure, all patients are measured at the beginning of the study, given a treatment, and measured again. Thus, each subject has two measures, often called before and after measures. Entering of data for paired test : Entering of data for paired test Slide 13: One-Way ANOVA
The One-Way ANOVA procedure produces a one-way analysis of variance for a quantitative dependent variable by a single factor (independent) variable. Analysis of variance is used to test the hypothesis that several means are equal. This technique is an extension of the two-sample t test. One way anova : One way anova One way anova evaluate the equality of several population means Slide 15: compare means
normaly distributed large sample small size
(by K-S TEST)
One sample T test
2 sample T test pooled paired
One way anova more than 2 sample