The workflow of data analysis using stata:
Saved in:
| Main Author: | |
|---|---|
| Format: | Book |
| Language: | English |
| Published: |
College Station, Texas
Stata Press
2009
|
| Edition: | First edition |
| Series: | A Stata Press publication
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| Subjects: | |
| Online Access: | Inhaltsverzeichnis |
| Physical Description: | xxxi, 379 Seiten Diagramme |
| ISBN: | 9781597180474 |
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MARC
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| 245 | 1 | 0 | |a The workflow of data analysis using stata |c J. Scott Long |
| 250 | |a First edition | ||
| 264 | 1 | |a College Station, Texas |b Stata Press |c 2009 | |
| 300 | |a xxxi, 379 Seiten |b Diagramme | ||
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Record in the Search Index
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IMAGE 1
CONTENTS
LIST OF TABLES XXI
LIST OF FIGURES XXIII
LIST OF EXAMPLES XXV
PREFACE XXIX
A WORD ABOUT FONTS, FILES, COMMANDS, AND EXAMPLES XXXIII
INTRODUCTION 1
1.1 REPLICATION: THE GUIDING PRINCIPLE FOR WORKFLOW 2
1.2 STEPS IN THE WORKFLOW 3
1.2.1 CLEANING DATA 4
1.2.2 RUNNING ANALYSIS 4
1.2.3 PRESENTING RESULTS 4
1.2.4 PROTECTING FILES 4
1.3 TASKS WITHIN EACH STEP 5
1.3.1 PLANNING 5
1.3.2 ORGANIZATION 5
1.3.3 DOCUMENTATION 5
1.3.4 EXECUTION 6
1.4 CRITERIA FOR CHOOSING A WORKFLOW 6
1.4.1 ACCURACY 6
1.4.2 EFFICIENCY 6
1.4.3 SIMPLICITY 7
1.4.4 STANDARDIZATION 7
1.4.5 AUTOMATION 7
1.4.6 USABILITY 7
IMAGE 2
1.4.7 SCALABILITY 8
1.5 CHANGING YOUR WORKFLOW 8
1.6 HOW THE BOOK IS ORGANIZED 8
PLANNING, ORGANIZING, AND DOCUMENTING 11
2.1 THE CYCLE OF DATA ANALYSIS 13
2.2 PLANNING 14
2.3 ORGANIZATION 18
2.3.1 PRINCIPLES FOR ORGANIZATION 18
2.3.2 ORGANIZING FILES AND DIRECTORIES 19
2.3.3 CREATING YOUR DIRECTORY STRUCTURE 21
A DIRECTORY STRUCTURE FOR A SMALL PROJECT 21
A DIRECTORY STRUCTURE FOR A LARGE, ONE-PERSON PROJECT . . . 23
DIRECTORIES FOR COLLABORATIVE PROJECTS 23
SPECIAL-PURPOSE DIRECTORIES 25
REMEMBERING WHAT DIRECTORIES CONTAIN 27
PLANNING YOUR DIRECTORY STRUCTURE 29
NAMING FILES 30
BATCH FILES 30
2.3.4 MOVING INTO A NEW DIRECTORY STRUCTURE (ADVANCED TOPIC) . . 31
EXAMPLE OF MOVING INTO A NEW DIRECTORY STRUCTURE 31
2.4 DOCUMENTATION 34
2.4.1 WHAT SHOULD YOU DOCUMENT? , . 36
2.4.2 LEVELS OF DOCUMENTATION 37
2.4.3 SUGGESTIONS FOR WRITING DOCUMENTATION 38
EVALUATING YOUR DOCUMENTATION 39
2.4.4 THE RESEARCH LOG 39
A SAMPLE PAGE FROM A RESEARCH LOG 40
A TEMPLATE FOR RESEARCH LOGS 42
2.4.5 CODEBOOKS 43
A CODEBOOK BASED ON THE SURVEY INSTRUMENT 43
IMAGE 3
2.4.6 DATASET DOCUMENTATION 44
2.5 CONCLUSIONS 45
WRITING AND DEBUGGING DO-FILES 47
3.1 THREE WAYS TO EXECUTE COMMANDS 47
3.1.1 THE COMMAND WINDOW 48
3.1.2 DIALOG BOXES 49
3.1.3 DO-FILES 49
3.2 WRITING EFFECTIVE DO-FILES 50
3.2.1 MAKING DO-FILES ROBUST 51
MAKE DO-FILES SELF-CONTAINED 51
USE VERSION CONTROL 53
EXCLUDE DIRECTORY INFORMATION 53
INCLUDE SEEDS FOR RANDOM NUMBERS . 55
3.2.2 MAKING DO-FILES LEGIBLE 55
USE LOTS OF COMMENTS 56
USE ALIGNMENT AND INDENTATION 57
USE SHORT LINES 58
LIMIT YOUR ABBREVIATIONS 61
BE CONSISTENT 63
3.2.3 TEMPLATES FOR DO-FILES 63
COMMANDS THAT BELONG IN EVERY DO-FILE 63
A TEMPLATE FOR SIMPLE DO-FILES 66
A MORE COMPLEX DO-FILE TEMPLATE 66
3.3 DEBUGGING DO-FILES 68
3.3.1 SIMPLE ERRORS AND HOW TO FIX THEM 68
LOG FILE IS OPEN 68
LOG FILE ALREADY EXISTS 68
INCORRECT COMMAND NAME 69
INCORRECT VARIABLE NAME 69
IMAGE 4
INCORRECT OPTION 70
MISSING COMMA BEFORE OPTIONS 70
3.3.2 STEPS FOR RESOLVING ERRORS 70
STEP 1: UPDATE STATA AND USER-WRITTEN PROGRAMS 70
STEP 2: START WITH A CLEAN SLATE 71
STEP 3: TRY OTHER DATA 72
STEP 4: ASSUME EVERYTHING COULD BE WRONG 72
STEP 5: RUN THE PROGRAM IN STEPS 72
STEP 6: EXCLUDE PARTS OF THE DO-FILE 74
STEP 7: STARTING OVER 74
STEP 8: SOMETIMES IT IS NOT YOUR MISTAKE 75
3.3.3 EXAMPLE 1: DEBUGGING A SUBTLE SYNTAX ERROR 75
3.3.4 EXAMPLE 2: DEBUGGING UNANTICIPATED RESULTS 77
3.3.5 ADVANCED METHODS FOR DEBUGGING 81
3.4 HOW TO GET HELP 82
3.5 CONCLUSIONS 82
AUTOMATING YOUR WORK 83
4.1 MACROS 83
4.1.1 LOCAL AND GLOBAL MACROS 84
LOCAL MACROS 84
GLOBAL MACROS 85
USING DOUBLE QUOTES WHEN DEFINING MACROS 85
CREATING LONG STRINGS 85
4.1.2 SPECIFYING GROUPS OF VARIABLES AND NESTED MODELS 86
4.1.3 SETTING OPTIONS WITH LOCALS 88
4.2 INFORMATION RETURNED BY STATA COMMANDS 90
USING RETURNED RESULTS WITH LOCAL MACROS 92
4.3 LOOPS: FOREACH AND FORVALUES 92
THE FOREACH COMMAND 94
THE FORVALUES COMMAND 95
IMAGE 5
4.3.1 WAYS TO USE LOOPS 95
LOOP EXAMPLE 1: LISTING VARIABLE AND VALUE LABELS 96
LOOP EXAMPLE 2: CREATING INTERACTION VARIABLES 97
LOOP EXAMPLE 3: FITTING MODELS WITH ALTERNATIVE MEA- SURES OF EDUCATION
98
LOOP EXAMPLE 4: RECODING MULTIPLE VARIABLES THE SAME WAY 98
LOOP EXAMPLE 5: CREATING A MACRO THAT HOLDS ACCUMU- LATED INFORMATION 99
LOOP EXAMPLE 6: RETRIEVING INFORMATION RETURNED BY STATA . 100
4.3.2 COUNTERS IN LOOPS 101
USING LOOPS TO SAVE RESULTS TO A MATRIX 102
4.3.3 NESTED LOOPS 104
4.3.4 DEBUGGING LOOPS 105
4.4 THE INCLUDE COMMAND 106
4.4.1 SPECIFYING THE ANALYSIS SAMPLE WITH AN INCLUDE FILE 107
4.4.2 RECODING DATA USING INCLUDE FILES 107
4.4.3 CAUTION WHEN USING INCLUDE FILES 109
4.5 ADO-FILES 110
4.5.1 A SIMPLE PROGRAM TO CHANGE DIRECTORIES I LL
4.5.2 LOADING AND DELETING ADO-FILES 112
4.5.3 LISTING VARIABLE NAMES AND LABELS 113
4.5.4 A GENERAL PROGRAM TO CHANGE YOUR WORKING DIRECTORY . . . 117
4.5.5 WORDS OF CAUTION 118
4.6 HELP FILES 119
4.6.1 NMLABEL.HLP 119
4.6.2 HELP ME 122
4.7 CONCLUSIONS 123
N A M E S, N O T E S, A ND L A B E LS 125
5.1 POSTING FILES 125
5.2 T HE DUAL WORKFLOW OF D A TA MANAGEMENT AND STATISTICAL ANALYSIS .
. 127
5.3 NAMES, NOTES, AND LABELS 129
IMAGE 6
5.4 NAMING DO-FILES 129
5.4.1 NAMING DO-FILES TO RE-CREATE DATASETS 130
5.4.2 NAMING DO-FILES TO REPRODUCE STATISTICAL ANALYSIS 130
5.4.3 USING MASTER DO-FILES 131
MASTER LOG FILES 133
5.4.4 A TEMPLATE FOR NAMING DO-FILES 134
USING SUBDIRECTORIES FOR COMPLEX ANALYSES 135
5.5 NAMING AND INTERNALLY DOCUMENTING DATASETS 136
NEVER NAME IT FINAL! 137
5.5.1 ONE TIME ONLY AND TEMPORARY DATASETS 137
5.5.2 DATASETS FOR LARGER PROJECTS 138
5.5.3 LABELS AND NOTES FOR DATASETS 138
5.5.4 THE DATASIGNATURE COMMAND 139
A WORKFLOW USING THE DATASIGNATURE COMMAND 140
CHANGES DATASIGNATURE DOES NOT DETECT 141
5.6 NAMING VARIABLES 143
5.6.1 THE FUNDAMENTAL PRINCIPLE FOR CREATING AND NAMING VARIABLES 143
5.6.2 SYSTEMS FOR NAMING VARIABLES 144
SEQUENTIAL NAMING SYSTEMS 145
SOURCE NAMING SYSTEMS 145
MNEMONIC NAMING SYSTEMS 146
5.6.3 PLANNING NAMES 146
5.6.4 PRINCIPLES FOR SELECTING NAMES 147
ANTICIPATE LOOKING FOR VARIABLES 147
USE SIMPLE, UNAMBIGUOUS NAMES 148
TRY NAMES BEFORE YOU DECIDE 151
5.7 LABELING VARIABLES 151
5.7.1 LISTING VARIABLE LABELS AND OTHER INFORMATION 151
CHANGING THE ORDER OF VARIABLES IN YOUR DATASET 155
5.7.2 SYNTAX FOR LABEL VARIABLE 155
IMAGE 7
5.7.3 PRINCIPLES FOR VARIABLE LABELS 156
BEWARE OF TRUNCATION 156
TEST LABELS BEFORE YOU POST THE FILE 157
5.7.4 TEMPORARILY CHANGING VARIABLE LABELS 157
5.7.5 CREATING VARIABLE LABELS THAT INCLUDE THE VARIABLE NAME . . . 158
5.8 ADDING NOTES TO VARIABLES 160
5.8.1 COMMANDS FOR WORKING WITH NOTES 161
LISTING NOTES 161
REMOVING NOTES 162
SEARCHING NOTES 162
5.8.2 USING MACROS AND LOOPS WITH NOTES 162
5.9 VALUE LABELS 163
5.9.1 CREATING VALUE LABELS IS A TWO-STEP PROCESS 164
STEP 1: DEFINING LABELS 164
STEP 2: ASSIGNING LABELS 164
WHY A TWO-STEP SYSTEM? 164
REMOVING LABELS 165
5.9.2 PRINCIPLES FOR CONSTRUCTING VALUE LABELS 165
1) KEEP LABELS SHORT 165
2) INCLUDE THE CATEGORY NUMBER 166
3) AVOID SPECIAL CHARACTERS 168
4) KEEPING TRACK OF WHERE LABELS ARE USED 169
5.9.3 CLEANING VALUE LABELS 170
5.9.4 CONSISTENT VALUE LABELS FOR MISSING VALUES 171
5.9.5 USING LOOPS WHEN ASSIGNING VALUE LABELS 171
5.10 USING MULTIPLE LANGUAGES 173
5.10.1 USING LABEL LANGUAGE FOR DIFFERENT WRITTEN LANGUAGES 174
5.10.2 USING LABEL LANGUAGE FOR SHORT AND LONG LABELS 174
5.11 A WORKFLOW FOR NAMES AND LABELS 176
STEP 1: PLAN THE CHANGES 176
IMAGE 8
STEP 2: ARCHIVE, CLONE, AND RENAME 177
STEP 3: REVISE VARIABLE LABELS 177
STEP 4: REVISE VALUE LABELS 177
STEP 5: VERIFY THE CHANGES 178
5.11.1 STEP 1: CHECK THE SOURCE DATA 178
STEP LA: LIST THE CURRENT NAMES AND LABELS 178
STEP LB: TRY THE CURRENT NAMES AND LABELS 181
5.11.2 STEP 2: CREATE CLONES AND RENAME VARIABLES 182
STEP 2A: CREATE CLONES 183
STEP 2B: CREATE RENAME COMMANDS 183
STEP 2C: RENAME VARIABLES 184
5.11.3 STEP 3: REVISE VARIABLE LABELS 185
STEP 3A: CREATE VARIABLE-LABEL COMMANDS 185
STEP 3B: REVISE VARIABLE LABELS 186
5.11.4 STEP 4: REVISE VALUE LABELS 187
STEP 4A: LIST THE CURRENT LABELS 188
STEP 4B: CREATE LABEL DEFINE COMMANDS TO EDIT 189
STEP 4C: REVISE LABELS AND ADD THEM TO DATASET 193
5.11.5 STEP 5: CHECK THE NEW NAMES AND LABELS 194
5.12 CONCLUSIONS 195
CLEANING YOUR DATA 197
6.1 IMPORTING DATA 198
6.1.1 DATA FORMATS 198
ASCII DATA FORMATS 198
BINARY-DATA FORMATS 200
6.1.2 WAYS TO IMPORT DATA 201
STATA COMMANDS TO IMPORT DATA 201
USING OTHER STATISTICAL PACKAGES TO EXPORT DATA 203
USING A DATA CONVERSION PROGRAM 203
IMAGE 9
6.1.3 VERIFYING DATA CONVERSION 203
CONVERTING THE ISSP 2002 DATA FROM RUSSIA 204
6.2 VERIFYING VARIABLES 210
6.2.1 VALUES REVIEW 211
VALUES REVIEW OF DATA ABOUT THE SCIENTIFIC CAREER 212
VALUES REVIEW OF DATA ON FAMILY VALUES 215
6.2.2 SUBSTANTIVE REVIEW 216
WHAT DOES TIME TO DEGREE MEASURE? 216
EXAMINING HIGH-FREQUENCY VALUES 218
LINKS AMONG VARIABLES 220
CHANGES IN SURVEY QUESTIONS 225
6.2.3 MISSING-DATA REVIEW 225
COMPARISONS AND MISSING VALUES 225
CREATING INDICATORS OF WHETHER CASES ARE MISSING 228
USING EXTENDED MISSING VALUES 228
VERIFYING AND EXPANDING MISSING-DATA CODES 229
USING INCLUDE FILES 236
6.2.4 INTERNAL CONSISTENCY REVIEW 238
CONSISTENCY IN DATA ON THE SCIENTIFIC CAREER 238
6.2.5 PRINCIPLES FOR FIXING DATA INCONSISTENCIES 241
6.3 CREATING VARIABLES FOR ANALYSIS 241
6.3.1 PRINCIPLES FOR CREATING NEW VARIABLES 242
NEW VARIABLES GET NEW NAMES 242
VERIFY THAT NEW VARIABLES ARE CORRECT 243
DOCUMENT NEW VARIABLES 244
KEEP THE SOURCE VARIABLES 244
6.3.2 CORE COMMANDS FOR CREATING VARIABLES 244
THE GENERATE COMMAND 245
THE CLONEVAR COMMAND 245
THE REPLACE COMMAND 246
IMAGE 10
6.3.3 CREATING VARIABLES WITH MISSING VALUES 247
6.3.4 ADDITIONAL COMMANDS FOR CREATING VARIABLES 249
THE RECODE COMMAND 249
THE EGEN COMMAND 250
THE TABULATE, GENERATE() COMMAND 252
6.3.5 LABELING VARIABLES CREATED BY STATA 253
6.3.6 VERIFYING THAT VARIABLES ARE CORRECT 254
CHECKING THE CODE 255
LISTING VARIABLES 255
PLOTTING CONTINUOUS VARIABLES 256
TABULATING VARIABLES 258
CONSTRUCTING VARIABLES MULTIPLE WAYS 259
6.4 SAVING DATASETS 260
6.4.1 SELECTING OBSERVATIONS 261
DELETING CASES VERSUS CREATING SELECTION VARIABLES 261
6.4.2 DROPPING VARIABLES 262
SELECTING VARIABLES FOR THE ISSP 2002 RUSSIAN DATA 263
6.4.3 ORDERING VARIABLES 263
6.4.4 INTERNAL DOCUMENTATION 264
6.4.5 COMPRESSING VARIABLES 264
6.4.6 RUNNING DIAGNOSTICS 265
THE CODEBOOK, PROBLEMS COMMAND . 265
CHECKING FOR UNIQUE ID VARIABLES 267
6.4.7 ADDING A DATA SIGNATURE 269
6.4.8 SAVING THE FILE 270
6.4.9 AFTER A FILE IS SAVED 271
6.5 EXTENDED EXAMPLE OF PREPARING DATA FOR ANALYSIS 271
CREATING CONTROL VARIABLES 271
CREATING BINARY INDICATORS OF POSITIVE ATTITUDES 274
CREATING FOUR-CATEGORY SCALES OF POSITIVE ATTITUDES 277
IMAGE 11
6.6 MERGING FILES 279
6.6.1 MATCH-MERGING 280
SORTING THE ID VARIABLE 281
6.6.2 ONE-TO-ONE MERGING 281
COMBINING UNRELATED DATASETS 281
6.6.3 FORGETTING TO MATCH-MERGE 283
6.7 CONCLUSIONS 285
ANALYZING DATA AND PRESENTING RESULTS 287
7.1 PLANNING AND ORGANIZING STATISTICAL ANALYSIS 287
7.1.1 PLANNING IN THE LARGE 288
7.1.2 PLANNING IN THE MIDDLE 289
7.1.3 PLANNING IN THE SMALL 291
7.2 ORGANIZING DO-FILES 291
7.2.1 USING MASTER DO-FILES 292
7.2.2 WHAT BELONGS IN YOUR DO-FILE? 294
7.3 DOCUMENTATION FOR STATISTICAL ANALYSIS 295
7.3.1 THE RESEARCH LOG AND COMMENTS IN DO-FILES 295
7.3.2 DOCUMENTING THE PROVENANCE OF RESULTS 296
CAPTIONS ON GRAPHS 298
7.4 ANALYZING DATA USING AUTOMATION 298
7.4.1 LOCALS TO DEFINE SETS OF VARIABLES 299
7.4.2 LOOPS FOR REPEATED ANALYSES 300
COMPUTING T TESTS USING LOOPS 300
LOOPS FOR ALTERNATIVE MODEL SPECIFICATIONS 302
7.4.3 MATRICES TO COLLECT AND PRINT RESULTS 303
COLLECTING RESULTS OF T TESTS 303
SAVING RESULTS FROM NESTED REGRESSIONS 306
SAVING RESULTS FROM DIFFERENT TRANSFORMATIONS OF ARTICLES . . . 308
7.4.4 CREATING A GRAPH FROM A MATRIX 310
7.4.5 INCLUDE FILES TO LOAD DATA AND SELECT YOUR SAMPLE 311
IMAGE 12
7.5 BASELINE STATISTICS 312
7.6 REPLICATION 313
7.6.1 LOST OR FORGOTTEN FILES 313
7.6.2 SOFTWARE AND VERSION CONTROL 314
7.6.3 UNKNOWN SEED FOR RANDOM NUMBERS 314
BOOTSTRAP STANDARD ERRORS 314
LETTING STATA SET THE SEED 315
TRAINING AND CONFIRMATION SAMPLES 316
7.6.4 USING A GLOBAL THAT IS NOT IN YOUR DO-FILE 318
7.7 PRESENTING RESULTS 318
7.7.1 CREATING TABLES 319
USING SPREADSHEETS 319
REGRESSION TABLES WITH ESTTAB 321
7.7.2 CREATING GRAPHS 323
COLORS, BLACK, AND WHITE 324
FONT SIZE 326
7.7.3 TIPS FOR PAPERS AND PRESENTATIONS 326
PAPERS 326
PRESENTATIONS 327
7.8 A PROJECT CHECKLIST 328
7.9 CONCLUSIONS 328
8 PROTECTING YOUR FILES 331
8.1 LEVELS OF PROTECTION AND TYPES OF FILES 332
8.2 CAUSES OF DATA LOSS AND ISSUES IN RECOVERING A FILE 334
8.3 MURPHY'S LAW AND RULES FOR COPYING FILES 337
8.4 A WORKFLOW FOR FILE PROTECTION 338
PART 1: MIRRORING ACTIVE STORAGE 338
PART 2: OFFLINE BACKUPS 340
8.5 ARCHIVAL PRESERVATION 343
8.6 CONCLUSIONS 345
IMAGE 13
9 CONCLUSIONS 347
A HOW STATA WORKS 349
A.I HOW STATA WORKS 349
STATA DIRECTORIES 350
THE WORKING DIRECTORY 350
A.2 WORKING ON A NETWORK 351
A.3 CUSTOMIZING STATA 353
A.3.1 FONTS AND WINDOW LOCATIONS 353
A.3.2 COMMANDS TO CHANGE PREFERENCES 353
OPTIONS THAT CAN BE SET PERMANENTLY 353
OPTIONS THAT NEED TO BE SET EACH SESSION 355
A.3.3 PROFILE.DO 355
FUNCTION KEYS 356
A.4 ADDITIONAL RESOURCES 356
REFERENCES 359
AUTHOR INDEX 363
SUBJECT INDEX 365 |
| any_adam_object | 1 |
| author | Long, J. Scott |
| author_GND | (DE-588)171773071 |
| author_facet | Long, J. Scott |
| author_role | aut |
| author_sort | Long, J. Scott |
| author_variant | j s l js jsl |
| building | Verbundindex |
| bvnumber | BV035209456 |
| callnumber-first | Q - Science |
| callnumber-label | QA276 |
| callnumber-raw | QA276.45.S73 |
| callnumber-search | QA276.45.S73 |
| callnumber-sort | QA 3276.45 S73 |
| callnumber-subject | QA - Mathematics |
| classification_rvk | MR 2100 ST 601 |
| classification_tum | MAT 627f SOZ 720f DAT 307f |
| ctrlnum | (OCoLC)698938082 (DE-599)BSZ286127598 |
| dewey-full | 519.50285536922 |
| dewey-hundreds | 500 - Natural sciences and mathematics |
| dewey-ones | 519 - Probabilities and applied mathematics |
| dewey-raw | 519.50285536922 |
| dewey-search | 519.50285536922 |
| dewey-sort | 3519.50285536922 |
| dewey-tens | 510 - Mathematics |
| discipline | Informatik Soziologie Mathematik |
| edition | First edition |
| format | Book |
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| id | DE-604.BV035209456 |
| illustrated | Not Illustrated |
| indexdate | 2024-09-06T00:15:28Z |
| institution | BVB |
| isbn | 9781597180474 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-017015702 |
| oclc_num | 698938082 |
| open_access_boolean | |
| owner | DE-473 DE-BY-UBG DE-19 DE-BY-UBM DE-N2 DE-91 DE-BY-TUM DE-384 DE-Re13 DE-BY-UBR DE-M347 DE-945 DE-188 DE-11 DE-634 DE-20 |
| owner_facet | DE-473 DE-BY-UBG DE-19 DE-BY-UBM DE-N2 DE-91 DE-BY-TUM DE-384 DE-Re13 DE-BY-UBR DE-M347 DE-945 DE-188 DE-11 DE-634 DE-20 |
| physical | xxxi, 379 Seiten Diagramme |
| publishDate | 2009 |
| publishDateSearch | 2009 |
| publishDateSort | 2009 |
| publisher | Stata Press |
| record_format | marc |
| series2 | A Stata Press publication |
| spelling | Long, J. Scott Verfasser (DE-588)171773071 aut The workflow of data analysis using stata J. Scott Long First edition College Station, Texas Stata Press 2009 xxxi, 379 Seiten Diagramme txt rdacontent n rdamedia nc rdacarrier A Stata Press publication Datenanalyse (DE-588)4123037-1 gnd rswk-swf Stata (DE-588)4617285-3 gnd rswk-swf Stata (DE-588)4617285-3 s Datenanalyse (DE-588)4123037-1 s b DE-604 SWB Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=017015702&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Long, J. Scott The workflow of data analysis using stata Datenanalyse (DE-588)4123037-1 gnd Stata (DE-588)4617285-3 gnd |
| subject_GND | (DE-588)4123037-1 (DE-588)4617285-3 |
| title | The workflow of data analysis using stata |
| title_auth | The workflow of data analysis using stata |
| title_exact_search | The workflow of data analysis using stata |
| title_full | The workflow of data analysis using stata J. Scott Long |
| title_fullStr | The workflow of data analysis using stata J. Scott Long |
| title_full_unstemmed | The workflow of data analysis using stata J. Scott Long |
| title_short | The workflow of data analysis using stata |
| title_sort | the workflow of data analysis using stata |
| topic | Datenanalyse (DE-588)4123037-1 gnd Stata (DE-588)4617285-3 gnd |
| topic_facet | Datenanalyse Stata |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=017015702&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
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