Introduction to Stata 8

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15.5. Immediate commands [U] 22 An 'immediate' command requires tabular or aggregated input; data in memory are not affected. The immediate commands tabi, cci, csi, iri and ttesti are mentioned in section 11, and sampsi (sample size estimation) in section 15.6. Confidence intervals [R] ci The general command ci and the 'immediate command cii calculate confidence intervals. I here show the use of cii: Normal distribution: cii 372 37.58 16.51 N mean SD Binomial distribution: cii 153 40 N events Poisson distribution: cii 247.1 40 , poisson time events Stata as a pocket calculator [R] display The display command gives the opportunity to perform calculations not affecting the data in memory (_pi is a Stata constant): . display 2*_pi*7 43.982297 You may include an explanatory text: . display "The circumference of a circle with radius 7 is " 2*_pi*7 The circumference of a circle with radius 7 is 43.982297 60
15.6. Sample size and study power sampsi [R] sampsi Sample size and study power estimation are pre-study activities: What are the consequences of different decisions and assumptions for sample size and study power? You must make these decisions: • The desired significance level (α). Default: 0.05. • The minimum relevant contrast – expressed as study group means or proportions. • Sample size estimation: The desired power (1–β). Default: 0.90. • Power estimation: Sample sizes. And with comparison of means you must make an assumption: • The assumed standard deviation in each sample. Here are short examples for the four main scenarios: Comparison of: Sample size estimation Power estimation Proportions sampsi 0.4 0.5 sampsi 0.4 0.5 , n(60) Means sampsi 50 60 , sd(8) sampsi 50 60 , sd(8) n(60) Further options are available: Situation Option 61 Sample size Power prop. mean prop. mean Significance level; default: 0.05 alpha(0.01) + + + + Power; default: 0.90 power(0.95) + + Unequal sample sizes; ratio=n2/n1 ratio(2) + + Unequal sample sizes n1(40) n2(80) + + Unequal SDs sd1(6) sd2(9) + + Example: Sample size estimation for comparison of means, unequal SDs and sample sizes: sampsi 50 60 , sd1(14) sd2(10) ratio(2) sampsi also handles trials with repeated measurements, see [R] sampsi.
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Introduction to Stata 8 Svend Juul
Page 3 and 4:
Preface Stata is a software package
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1. Installing, customizing and upda
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2. Windows in Stata [GSW] 2 I Sugge
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3. Suggested mode of operation The
Page 11 and 12: 4. Getting help [GSW] 4, 19, 20; [U
Page 13 and 14: 6. Variables A Stata data set is re
Page 15 and 16: 7. Command syntax [U] 14.1 Stata is
Page 17 and 18: y and bysort prefix [U] 14.5 Makes
Page 19 and 20: Reading ASCII data [U] 24 Reading t
Page 21 and 22: See label definitions See the value
Page 23 and 24: generate; replace [R] generate Gene
Page 25 and 26: 10.2. Selections Selecting observat
Page 27 and 28: 10.6. Combining files [U] 25 Append
Page 29 and 30: 11. Description and analysis This s
Page 31 and 32: tabi [R] tabulate tabi is an 'immed
Page 33 and 34: ttest [R] ttest T-test for comparis
Page 35 and 36: 12.2. Logistic regression logistic
Page 37 and 38: . summarize Variable | Obs Mean Std
Page 39 and 40: poisson [R] poisson The stsplit.can
Page 41 and 42: 14.2. The anatomy of graphs Figure
Page 43 and 44: Ticks, labels and gridlines Stata s
Page 45 and 46: The default connect-style is a stra
Page 47 and 48: In bar graphs the x-axis is categor
Page 49 and 50: twoway connected; twoway rcap Mean
Page 51 and 52: twoway dropline Patient number 20 1
Page 53 and 54: graph matrix 40 30 20 10 250 200 15
Page 55 and 56: Select Enhanced Metafile (EMF) or W
Page 57 and 58: 15.2. String variables [U] 15.4; [U
Page 59 and 60: 15.3. Dates. Danish CPR numbers Dat
Page 61: 15.4. Random samples, simulations R
Page 65 and 66: 15.8. Exchange of data with other p
Page 67 and 68: 16. Do-file examples Here follow sh
Page 69 and 70: Appendix 1 Purchasing Stata and man
Page 71 and 72: Variable names can have up to 8 cha
Page 73 and 74: Index A ado-files .................
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