Data Management Using Stata

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Opis: Data Management Using Stata - Michael Mitchell

Using simple language and illustrative examples, this book comprehensively covers data management tasks that bridge the gap between raw data and statistical analysis. Rather than focus on clusters of commands, the author takes a modular approach that enables readers to quickly identify and implement the necessary task without having to access background information first. Each section in the chapters presents a self-contained lesson that illustrates a particular data management task via examples, such as creating data variables and automating error checking. The text also discusses common pitfalls and how to avoid them and provides strategic data management advice. Ideal for both beginning statisticians and experienced users, this handy book helps readers solve problems and learn comprehensive data management skills. The author uses a "learning by example" approach in the book. Overall this works well ... -Morteza Marzjarani, The American Statistician, November 2011Introduction Using this book Overview of this book Listing observations in this book Reading and Writing Datasets Introduction Reading Stata datasets Saving Stata datasets Reading comma-separated and tab-separated files Reading space-separated files Reading fixed-column files Reading fixed-column files with multiple lines of raw data per observation Reading SAS XPORT files Common errors reading files Entering data directly into the Stata Data Editor Saving comma-separated and tab-separated files Saving space-separated files Saving SAS XPORT files Data Cleaning Introduction Double data entry Checking individual variables Checking categorical by categorical variables Checking categorical by continuous variables Checking continuous by continuous variables Correcting errors in data Identifying duplicates Final thoughts on data cleaning Labeling Datasets Introduction Describing datasets Labeling variables Labeling values Labeling utilities Labeling variables and values in different languages Adding comments to your dataset using notes Formatting the display of variables Changing the order of variables in a dataset Creating Variables Introduction Creating and changing variables Numeric expressions and functions String expressions and functions Recoding Coding missing values Dummy variables Date variables Date-and-time variables Computations across variables Computations across observations More examples using the egen command Converting string variables to numeric variables Converting numeric variables to string variables Renaming and ordering variables Combining Datasets Introduction Appending: Appending datasets Appending: Problems Merging: One-to-one match-merging Merging: One-to-many match-merging Merging: Merging multiple datasets Merging: Update merges Merging: Additional options when merging datasets Merging: Problems merging datasets Joining datasets Crossing datasets Processing Observations across Subgroups Introduction Obtaining separate results for subgroups Computing values separately by subgroups Computing values within subgroups: Subscripting observations Computing values within subgroups: Computations across observations Computing values within subgroups: Running sums Computing values within subgroups: More examples Comparing the by and tsset commands Changing the Shape of Your Data Introduction Wide and long datasets Introduction to reshaping long to wide Reshaping long to wide: Problems Introduction to reshaping wide to long Reshaping wide to long: Problems Multilevel datasets Collapsing datasets Programming for Data Management Introduction Tips on long-term goals in data management Executing do-files and making log files Automating data checking Combining do-files Introducing Stata macros Manipulating Stata macros Repeating commands by looping over variables Repeating commands by looping over numbers Repeating commands by looping over anything Accessing results saved from Stata commands Saving results of estimation commands as data Writing Stata programs Additional Resources Online resources for this book Finding and installing additional programs More online resources Appendix: Common elements Index


Szczegóły: Data Management Using Stata - Michael Mitchell

Tytuł: Data Management Using Stata
Autor: Michael Mitchell
Producent: Stata Press
ISBN: 9781597180764
Rok produkcji: 2010
Ilość stron: 387
Oprawa: Miękka
Waga: 0.79 kg


Recenzje: Data Management Using Stata - Michael Mitchell

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Inne pozycje tego autora: Michael Mitchell (1)

Data Management Using Stata

Using simple language and illustrative examples, this book comprehensively covers data management tasks that bridge the gap between raw data and statistical analysis. Rather than focus on clusters of commands, the author takes a modular approach that enables readers to quickly identify and implement the necessary task without having to access background information first. Each section in the chapters presents a self-contained lesson that illustrates a particular data management task via examples, such as creating data variables and automating error checking. The text also discusses common pitfalls and how to avoid them and provides strategic data management advice. Ideal for both beginning statisticians and experienced users, this handy book helps readers solve problems and learn comprehensive data management skills. The author uses a "learning by example" approach in the book. Overall this works well ... -Morteza Marzjarani, The American Statistician, November 2011Introduction Using this book Overview of this book Listing observations in this book Reading and Writing Datasets Introduction Reading Stata datasets Saving Stata datasets Reading comma-separated and tab-separated files Reading space-separated files Reading fixed-column files Reading fixed-column files with multiple lines of raw data per observation Reading SAS XPORT files Common errors reading files Entering data directly into the Stata Data Editor Saving comma-separated and tab-separated files Saving space-separated files Saving SAS XPORT files Data Cleaning Introduction Double data entry Checking individual variables Checking categorical by categorical variables Checking categorical by continuous variables Checking continuous by continuous variables Correcting errors in data Identifying duplicates Final thoughts on data cleaning Labeling Datasets Introduction Describing datasets Labeling variables Labeling values Labeling utilities Labeling variables and values in different languages Adding comments to your dataset using notes Formatting the display of variables Changing the order of variables in a dataset Creating Variables Introduction Creating and changing variables Numeric expressions and functions String expressions and functions Recoding Coding missing values Dummy variables Date variables Date-and-time variables Computations across variables Computations across observations More examples using the egen command Converting string variables to numeric variables Converting numeric variables to string variables Renaming and ordering variables Combining Datasets Introduction Appending: Appending datasets Appending: Problems Merging: One-to-one match-merging Merging: One-to-many match-merging Merging: Merging multiple datasets Merging: Update merges Merging: Additional options when merging datasets Merging: Problems merging datasets Joining datasets Crossing datasets Processing Observations across Subgroups Introduction Obtaining separate results for subgroups Computing values separately by subgroups Computing values within subgroups: Subscripting observations Computing values within subgroups: Computations across observations Computing values within subgroups: Running sums Computing values within subgroups: More examples Comparing the by and tsset commands Changing the Shape of Your Data Introduction Wide and long datasets Introduction to reshaping long to wide Reshaping long to wide: Problems Introduction to reshaping wide to long Reshaping wide to long: Problems Multilevel datasets Collapsing datasets Programming for Data Management Introduction Tips on long-term goals in data management Executing do-files and making log files Automating data checking Combining do-files Introducing Stata macros Manipulating Stata macros Repeating commands by looping over variables Repeating commands by looping over numbers Repeating commands by looping over anything Accessing results saved from Stata commands Saving results of estimation commands as data Writing Stata programs Additional Resources Online resources for this book Finding and installing additional programs More online resources Appendix: Common elements Index

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Cena 250,01 PLN
Nasza cena 233,75 PLN
Oszczędzasz 6%
Wysyłka: Niedostępna
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Szczegóły: Data Management Using Stata - Michael Mitchell

Tytuł: Data Management Using Stata
Autor: Michael Mitchell
Producent: Stata Press
ISBN: 9781597180764
Rok produkcji: 2010
Ilość stron: 387
Oprawa: Miękka
Waga: 0.79 kg


Recenzje: Data Management Using Stata - Michael Mitchell

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