Statistics A g r i Agricultural c u l t Statistical Data u r a l Analysis Using Stata S t a t i s Practical statistics is a powerful tool used frequently by agricultural researchers and t i graduate students involved in investigating experimental design and analysis. One c a of the most widely used statistical analysis software packages for this purpose is l Stata. The Stata software program has matured into a user-friendly environment D with a wide variety of statistical functions. Agricultural Statistical Data Analysis a Using Stata introduces readers to the use of Stata to solve agricultural statistical t a problems. A The book begins with an overview of statistical software and the Stata program. It n explains the various windows and menus and describes how they are integrated. The a l next chapters explore data entry and importing as well as basic output formats and y s descriptive statistics. The author describes the ever-increasing design complexity i s and how this is implemented in the software. He reviews one of Stata’s strongest U features, which is its programming ability. He also examines post hoc tests as well s as Stata’s graphing capabilities. The final chapters provide information on regression i n analysis, data transformations, and the analyses of nonparametric data. g Many agricultural researchers are unprepared for the statistics they will need to S use in their profession. Written in an easy-to-read format with screen shots and t a illustrations, the book is suitable for a wide audience, including beginners in statistics t a who are new to Stata, as well as more advanced Stata users and those interested in more complex designs. B o y h a n K20263 K20263_Cover.indd 1 5/8/13 9:50 AM Agricultural Statistical Data Analysis Using Stata George E. Boyhan CRC Press Taylor & Francis Group 6000 Broken Sound Parkway NW, Suite 300 Boca Raton, FL 33487-2742 © 2013 by Taylor & Francis Group, LLC CRC Press is an imprint of Taylor & Francis Group, an Informa business No claim to original U.S. Government works Version Date: 20130503 International Standard Book Number-13: 978-1-4665-8586-7 (eBook - PDF) This book contains information obtained from authentic and highly regarded sources. Reasonable efforts have been made to publish reliable data and information, but the author and publisher cannot assume responsibility for the validity of all materials or the consequences of their use. The authors and publishers have attempted to trace the copyright holders of all material reproduced in this publication and apologize to copyright holders if permission to publish in this form has not been obtained. If any copyright material has not been acknowledged please write and let us know so we may rectify in any future reprint. 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Visit the Taylor & Francis Web site at http://www.taylorandfrancis.com and the CRC Press Web site at http://www.crcpress.com To Dr. Norton who answered the phone over the Christmas holidays Contents IntroductIon vii About the Author xi chApter 1 GenerAl StAtIStIcAl pAckAGeS compArISonS 1 Program 3 Windows and Menus 4 What’s on the Menu? 13 Conclusion 27 chApter 2 dAtA entry 29 Importing Data 32 Manipulating Data and Formats 44 chApter 3 deScrIptIve StAtIStIcS 55 Output Formats 60 Experimentation Ideas 60 chApter 4 two SAmple teStS 63 ANOVA 69 Output and Meaning 71 chApter 5 vArIAtIonS of one fActor AnovA deSIGnS 75 Randomized Complete Block Design 75 Latin Square Designs 80 Balanced Incomplete Block Designs 84 Balanced Lattice Designs 88 Group Balanced Block Design 92 Subsampling 96 v vi Contents chApter 6 two And more fActorS AnovA 101 Split-Plot Design 106 Split-Block Design 109 Evaluation over Years or Seasons 114 Three-Factor Design 118 Split-Split Plot Design 120 Covariance Analysis 125 chApter 7 proGrAmmInG StAtA 133 chApter 8 poSt hoc teStS 147 Planned Comparisons 147 Built-in Multiple Range Tests 151 Programming Scheffé’s Test 157 chApter 9 prepArInG GrAphS 167 Graphing in Stata 167 chApter 10 correlAtIon And reGreSSIon 179 Correlation 179 Linear Regression 183 chApter 11 dAtA trAnSformAtIonS 203 chApter 12 bInAry, ordInAl, And cAteGorIcAl dAtA AnAlySIS 215 AppendIx 231 referenceS 237 Introduction Stata is a statistical software package that began as a command-line program. A graphical user interface (GUI) was added to the program sometime after its introduction, which has generally been very well executed. It allows beginners and novice users to conduct statistical procedures without having to type commands that can become rather complex with certain models. The command-line approach is never very far away and, as you gain confidence with the program, you will find yourself using it more and more. The program has matured into a user-friendly environment with a wide variety of statistical functions. A couple of nice features that have dramatically improved usability are being able to have a dataset visible on the desktop, while analyzing data and help menus that indicate where in the menus the specific statistical function can be found. This book will attempt to introduce the reader to using Stata to solve agricultural statistical problems. Stata, as a general purpose sta- tistical program, has a large suite of commands that are applicable in a variety of disciplines. Based on the number and scope of textbooks available on Stata, it has a strong following in medical, large popula- tion, and regression analyses. This is not to detract from its overall capabilities to solve a wide range of problems. vii viii IntroduCtIon This book provides an overview of using the Stata program. It includes a discussion of the various menus, many of the dialog boxes, and an explanation of how the parts are integrated. An explanation of how data can be entered into the program or imported is also presented. Surprisingly, for those new to statistical software and analyses, this can be one of the most time-consuming aspects of statistics. Stata has a very in-depth set of capabilities for entering, importing, and manipulating data prior to analyses. This is followed by a chapter on the simplest of descriptive statis- tics. An ever-increasing level of complexity as different models and approaches to agricultural statistical problems are introduced follows. One of the biggest changes in Stata is the ability to create graphs. This gives the Stata user another tool in preparing results for presentation and publication. This book attempts to explain how to use Stata to analyze agricul- tural experiments. Data that violate the underlying assumptions in many parametric tests must be handled differently. This may involve transformation or the use of nonparametric tests. Various examples from agricultural experiments are covered. Agricultural Statistical Data Analysis Using Stata includes the more important statistical procedures used in agricultural research. Various experimental designs and how to handle them within Stata are dis- cussed. Analysis of variance and covariance applications for agri- cultural experiments is covered. Post hoc tests and comparisons are covered as well. How to perform regression and correlations with some agricultural examples is included. The more important nonparametric tests used in agricultural research are also covered—in particular, the use of chi-square for cat- egorical data, such as from inheritance studies. As mentioned earlier, Stata grew out of a command-line inter- face, which is still recognizable as part of its foundation. In fact, this command-line interface is one of its strongest attributes because these commands can be organized and executed as a program, which expands the capabilities of Stata and ultimately makes things easier for users willing to devote some time to developing unique programs to solve their particular problems. An introduction to programming Stata is included, which should help users in this area. How to pro- gram Stata to extend its usability is also covered. Multiple-range tests