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Registros recuperados: 63
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Stata tip 55: Better axis labeling for time points and time intervals AgEcon
Cox, Nicholas J..
Tipo: Article Palavras-chave: Research Methods/ Statistical Methods.
Ano: 2007 URL: http://purl.umn.edu/119299
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A brief history of Stata on its 20th anniversary AgEcon
Cox, Nicholas J..
Tipo: Journal Article Palavras-chave: Research Methods/ Statistical Methods.
Ano: 2005 URL: http://purl.umn.edu/117491
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Stata tip 6: Inserting awkward characters in the plot AgEcon
Cox, Nicholas J..
Tipo: Journal Article Palavras-chave: Research Methods/ Statistical Methods.
Ano: 2004 URL: http://purl.umn.edu/116218
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Stata tip 65: Beware the backstabbing backslash AgEcon
Cox, Nicholas J..
Tipo: Article Palavras-chave: Research Methods/ Statistical Methods.
Ano: 2008 URL: http://purl.umn.edu/122606
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Review of Statistical Evaluation of Measurement Errors by Dunn AgEcon
Cox, Nicholas J..
This article reviews Statistical Evaluation of Measurement Errors by Dunn.
Tipo: Journal Article Palavras-chave: Measurement errors; Linear models; Mixed models; Gllamm; Research Methods/ Statistical Methods.
Ano: 2004 URL: http://purl.umn.edu/116280
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Speaking Stata: On numbers and strings AgEcon
Cox, Nicholas J..
The great divide among data types in Stata is between numeric and string variables. Most of the time, which kind you want to use for particular variables is clear and unproblematic, but surprisingly often, users face difficulties in making the right decision or need to convert variables from one kind to another. The main problems that may arise and their possible solutions are surveyed with reference both to official Stata and to user-written programs.
Tipo: Journal Article Palavras-chave: Binary variables; Categorical variables; Data Editor; Dates; Decode; Destring; Encode; Identifiers; Missing values; Numeric variables; Spreadsheets; String functions; String variables; Tostring; Value labels; Research Methods/ Statistical Methods.
Ano: 2002 URL: http://purl.umn.edu/116018
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Speaking Stata: Spineplots and their kin AgEcon
Cox, Nicholas J..
The term spineplot has been applied over the last decade or so to a type of bar chart used particularly for showing frequencies, proportions, or percentages of two cross-classified categorical variables. The principle is that the areas of rectangular tiles are proportional to the frequencies in the cells of a contingency table. Often both coarse and fine structure are easy to see, including departures from independence. The main idea has, in fact, been rediscovered repeatedly over at least the last 130 years. In its most general form, it has been widely publicized under the name mosaic plots. This column introduces, discusses, and exemplifies a Stata implementation of spineplots. It is noted that a restriction to two variables is more apparent than real,...
Tipo: Article Palavras-chave: Spineplots; Mosaic plots; Bar charts; Graphics; Categorical data; Research Methods/ Statistical Methods.
Ano: 2008 URL: http://purl.umn.edu/120931
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Speaking Stata: Graphing agreement and disagreement AgEcon
Cox, Nicholas J..
Many statistical problems involve comparison and, in particular, the assessment of agreement or disagreement between data measured on identical scales. Some commonly used plots are often ineffective in assessing the fine structure of such data, especially scatterplots of highly correlated variables and plots of values measured “before” and “after” using tilted line segments. Valuable alternatives are available using horizontal reference patterns, changes plotted as parallel lines, and parallel coordinates plots. The quantities of interest (usually differences on some scale) should be shown as directly as possible, and the responses of given individuals should be identified as easily as possible.
Tipo: Journal Article Palavras-chave: Graphics; Comparison; Agreement; Paired data; Panel data; Scatterplot; Difference-mean plot; Bland–Altman plot; Parallel lines plot; Parallel coordinates plot; Pairplot; Parplot; Linkplot; Tukey; Research Methods/ Statistical Methods.
Ano: 2004 URL: http://purl.umn.edu/116252
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Stata tip 62: Plotting on reversed scales AgEcon
Cox, Nicholas J.; Barlow, Natasha L.M..
Tipo: Article Palavras-chave: Research Methods/ Statistical Methods.
Ano: 2008 URL: http://purl.umn.edu/122594
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Speaking Stata: Identifying spells AgEcon
Cox, Nicholas J..
Spells in time series (and more generally in any kind of one-dimensional series) may be defined as sequences of observations that are homogeneous in some sense. For example, a categorical variable may remain in the same state, or values of a measured variable may satisfy the same true–false condition. Devices for working with spells in Stata include marking the start of each spell with indicator variables and tagging spells with integer codes. Panel data are easy to handle with the by: prefix. Some kinds of spell identification require two passes through the data, as when only spells of some minimum length are of interest or short gaps are tolerable within spells. Many questions concerning spells are easy to answer given careful use of by: and appropriate...
Tipo: Article Palavras-chave: Spells; Runs; Time series; Data management; Research Methods/ Statistical Methods.
Ano: 2007 URL: http://purl.umn.edu/119273
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Speaking Stata: On getting functions to do the work AgEcon
Cox, Nicholas J..
Functions in Stata take two main forms, built-in functions that are part of the executable and egen functions written in Stata’s own language. These are surveyed, giving a variety of tips and tricks, and noting the large number of user-written egen functions available for download from the Internet. Two substantial examples, the calculation of percentile ranks and plotting positions, and the calculation of measures summarizing properties of the other members of a group, provide detailed illustrations of egen in action.
Tipo: Journal Article Palavras-chave: Functions; Egen; Strings; Percentile ranks; Plotting positions; Family data; Research Methods/ Statistical Methods.
Ano: 2002 URL: http://purl.umn.edu/116026
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Speaking Stata: How to face lists with fortitude AgEcon
Cox, Nicholas J..
Three commands in official Stata, foreach, forvalues, and for, provide structures for cycling through lists of values (variable names, numbers, arbitrary text) and repeating commands using members of those lists in turn. All these commands may be used interactively, and none is restricted to use in Stata programs. They are explained and compared in some detail with a variety of examples. In addition, a self-contained exposition is given on local macros, understanding of which is needed for use of foreach and forvalues.
Tipo: Journal Article Palavras-chave: Foreach; Forvalues; For; Lists; Local macros; Substitution first; Research Methods/ Statistical Methods.
Ano: 2002 URL: http://purl.umn.edu/115962
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Speaking Stata: Rowwise AgEcon
Cox, Nicholas J..
Stata’s main data model treats observations in rows and variables in columns quite differently, but rowwise problems also arise that require working against the grain. This column shows how to exploit existing functions and egen functions when they exist and apply to such problems. It offers advice on how to build your own loops, egen functions, or programs when needed. Mata provides especially convenient tools for constructing many such functions and programs, centered on putting selected data into matrices and then processing each observation as a separate vector. Two programs, rowsort and rowranks, are formally published with this column.
Tipo: Article Palavras-chave: Rowsort; Rowranks; Rows; Functions; Loops; Egen; Mata; Minimum; Maximum; Median; Any; All; Distinct values; Sorting; Ranking; Research Methods/ Statistical Methods.
Ano: 2009 URL: http://purl.umn.edu/122706
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Stata tip 15: Function graphs on the fly AgEcon
Cox, Nicholas J..
Tipo: Journal Article Palavras-chave: Research Methods/ Statistical Methods.
Ano: 2004 URL: http://purl.umn.edu/116283
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Stata tip 9: Following special sequences AgEcon
Cox, Nicholas J..
Tipo: Journal Article Palavras-chave: Research Methods/ Statistical Methods.
Ano: 2004 URL: http://purl.umn.edu/116242
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Speaking Stata: Smoothing in various directions AgEcon
Cox, Nicholas J..
Identifying patterns in bivariate data on a scatterplot remains a basic statistical problem, with special avor when both variables are on the same footing. Ideas of double, diagonal, and polar smoothing inspired by Cleveland and McGill’s 1984 paper in the Journal of the American Statistical Association are revisited with various examples from environmental datasets. Double smoothing means smoothing both y given x and x given y. Diagonal smoothing means smoothing based on the sum and difference of y and x that treats the two variables symmetrically, possibly under standardization. Polar smoothing is based on the transformation from Cartesian to polar coordinates followed by smoothing and then reverse transformation; here the smoothing is implemented by...
Tipo: Journal Article Palavras-chave: Exploratory data analysis; Statistical graphics; Bivariate data; Double smoothing; Doublesm; Diagonal smoothing; Diagsm; Polar smoothing; Polarsm; Research Methods/ Statistical Methods.
Ano: 2005 URL: http://purl.umn.edu/117548
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Speaking Stata: Time of day AgEcon
Cox, Nicholas J..
Many problems in statistical analysis include time-of-day variables, but Stata offers limited support for time-of-day calculations. Support is needed for dates with times, times alone, and durations or timings. This article presents two new programs as general utilities to convert back and forth between string and numeric representations.
Tipo: Journal Article Palavras-chave: Ntimeofday; Stimeofday; Time of day; Time series; Calendar; Research Methods/ Statistical Methods.
Ano: 2006 URL: http://purl.umn.edu/117562
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Stata tip 17: Filling in the gaps AgEcon
Cox, Nicholas J..
Tipo: Journal Article Palavras-chave: Research Methods/ Statistical Methods.
Ano: 2005 URL: http://purl.umn.edu/117506
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Speaking Stata: How to repeat yourself without going mad AgEcon
Cox, Nicholas J..
This column will focus on how to improve your fluency in Stata. Over the next issues we will look at Stata problems of intermediate size which turn out to be soluble with a few command lines. As an introduction, systematic ways of repeating the same or similar operations are surveyed to give one overview of the territory to be covered.
Tipo: Journal Article Palavras-chave: Append; By; Collapse; Contract; Do-files; Egen; For; Foreach; Forvalues; Log files; Merge; Naming conventions; Programs; Repetition; Reshape; Statsby; Subset or group structure; Tabulations; Research Methods/ Statistical Methods.
Ano: 2001 URL: http://purl.umn.edu/115938
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Speaking Stata: Problems with tables, Part I AgEcon
Cox, Nicholas J..
Tables in some form or another are part and parcel of data management and analysis. The main general-purpose tabulation commands, tabulate, table, and tabstat, are reviewed and compared. When these do not provide a tabulation solution, one key strategy is to prepare the material for tabulation as a set of variables, after which the table itself can be presented with tabdisp or list. This is the first of two papers on this topic.
Tipo: Journal Article Palavras-chave: Tables; Tabulate; Table; Tabstat; Tabdisp; List; Research Methods/ Statistical Methods.
Ano: 2003 URL: http://purl.umn.edu/116122
Registros recuperados: 63
Primeira ... 1234 ... Última
 

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