start

This shows you the differences between two versions of the page.

Both sides previous revision Previous revision | Next revision Both sides next revision | ||

start [2022/07/29 10:44] 154.54.249.197 old revision restored (2022/03/31 04:37) |
start [2022/07/29 10:44] 154.54.249.197 old revision restored (2022/03/23 03:31) |
||
---|---|---|---|

Line 1: | Line 1: | ||

+ | [[sascode||SAScode]]|[[learnGerman]]| | ||

====== Generate Data from Graphs ====== | ====== Generate Data from Graphs ====== | ||

[[https:// | [[https:// | ||

Line 55: | Line 56: | ||

The key is to find the number of subjects that would let us gain the statistical power for the clincial trial. | The key is to find the number of subjects that would let us gain the statistical power for the clincial trial. | ||

- | =====Structure of Statistics===== | + | ************************************************************** |

+ | *** Interview Questions | ||

+ | ************************************************************** | ||

+ | | ||

+ | Randomized two arms, active and placebo | ||

+ | outcome variable y | ||

+ | measure twice, once baseline, once post treatment measurement. | ||

+ | Whether getting active improves y? | ||

+ | | ||

+ | You have two treatment groups and you have two measurements on each group. | ||

+ | | ||

+ | Best single answer: | ||

+ | Two measurements on placebo and active, what are you comparing on the t test? t test is just a simple test on the two groups' | ||

+ | 1. get change from the baseline for the placebo | ||

+ | 2. get change from the baseline fort the active. | ||

+ | Compare the mean difference of these two changes. | ||

+ | | ||

+ | 2nd method just to compare post treatment values: | ||

+ | Compare the mean differences between the two treatment results. | ||

+ | | ||

+ | Besides t test, we can use Anova, as with Anova we can use model, y(response, dependent variable)=treatment. | ||

+ | PROC ANOVA DATA=datasetname; | ||

+ | CLASS factorvars (such as treatment); | ||

+ | MODEL responsevar (such as change) = factorvars; * we can have baseline as covariate in the model | ||

+ | | ||

+ | If active has 10 observations, | ||

+ | | ||

+ | Outcome is 0, 1, how to determine the active is helping? | ||

+ | What if it's continuous variable, but not normally distributed, | ||

+ | | ||

+ | If you are doing Anova, what would you do? Does getting active treatment improve on outcome y? What is the model would be? | ||

+ | | ||

+ | What is the dependent variable in the ANOVA model? Left hand side is dependent variable | ||

+ | | ||

+ | In t test, the dependent variable could be the change from the baseline. | ||

+ | | ||

+ | The dependant variable is just the post treatment value or the change from the baseline, and explantory variable just is the treatment on the right hand side. | ||

+ | | ||

+ | Change from the baseline = treatment, the result exactly is the t test. | ||

+ | | ||

+ | Question: Suppose outcome variable y = 0, 1, or yes no, we got baseline and treatment, and we got some other variables, gender taking into account. | ||

+ | | ||

+ | Think more on the statistical side, not the programming side. | ||

+ | | ||

+ | | ||

+ | | ||

+ | ======Knowledge Structure of Biostatisticians====== | ||

+ | * theory: probability, | ||

+ | * applications: | ||

+ | * experimental design | ||

+ | * Environments / FDA regulations | ||

+ | * Software : SAS, R | ||

start.txt · Last modified: 2022/10/07 18:04 by 216.244.66.228