Regression models for categorical dependent variables using Stata:
Saved in:
| Main Authors: | , |
|---|---|
| Format: | Book |
| Language: | English |
| Published: |
College Station, Tex.
Stata Press
2006
|
| Edition: | 2. ed. |
| Series: | A Stata Press publication
|
| Subjects: | |
| Online Access: | Inhaltsverzeichnis Klappentext |
| Physical Description: | XXXII, 527 S. Ill., graph. Darst. |
| ISBN: | 9781597180115 1597180114 |
Staff View
MARC
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| 100 | 1 | |a Long, J. Scott |e Verfasser |0 (DE-588)171773071 |4 aut | |
| 245 | 1 | 0 | |a Regression models for categorical dependent variables using Stata |c J. Scott Long ; Jeremy Freese |
| 250 | |a 2. ed. | ||
| 264 | 1 | |a College Station, Tex. |b Stata Press |c 2006 | |
| 300 | |a XXXII, 527 S. |b Ill., graph. Darst. | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b n |2 rdamedia | ||
| 338 | |b nc |2 rdacarrier | ||
| 490 | 0 | |a A Stata Press publication | |
| 650 | 7 | |a Analisi della regressione - statistica |2 sbt | |
| 650 | 4 | |a Lehrbuch / Textbook - 28 | |
| 650 | 4 | |a Regression / Schätztheorie / PC-Software / Programmiersprache / Theorie | |
| 650 | 4 | |a Regressionsanalyse - Stata | |
| 650 | 7 | |a Stata - analisi della regressione |2 sbt | |
| 650 | 4 | |a Statistik | |
| 650 | 4 | |a Mathematical statistics | |
| 650 | 4 | |a Regression analysis | |
| 650 | 4 | |a Stata (Computer programs) | |
| 650 | 4 | |a Statistics | |
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| 689 | 0 | 1 | |a Stata |0 (DE-588)4617285-3 |D s |
| 689 | 0 | |5 DE-604 | |
| 700 | 1 | |a Freese, Jeremy |e Verfasser |0 (DE-588)1017211698 |4 aut | |
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Record in the Search Index
| _version_ | 1804135256097292288 |
|---|---|
| adam_text | Contents
Preface
I General Information
1
1.1
1.2
1.3
1.4
1.5
1.5.1
1.5.2
Installing SPost using search
Installing SPost using net install
1.5.3
1.5.4
1.5.5
1.5.6
1.6
2
2.1
Changing the scrollback buffer size
Changing the display of variable names in the Variables window
2.2
2.3
2.3.1
2.3.2
2.3.3
2.4
2.5
2.6
Options
2.6.1
2.6.2
2.6.3
2.7
2.7.1
2.7.2
2.7.3
2.8
2.9
2.9.1
2.9.2
2.9.3
2.9.4
Using Stata s Do-file Editor
Using other editors to create do-files
2.9.5
2.10
2.11
2.11.1
2.11.2
2.11.3
Examples of if qualifier
2.11.4
2.12
2.12.1
2.12.2
2.12.3
2.12.4
2.12.5
2.13
2.13.1
2.13.2
2.13.3
2.13.4
Breaking a categorical variable into a set of binary variables
More examples of creating binary variables
Nonlinear transformations
Interaction terms
2.14
2.14.1
2.14.2
2.14.3
2.15
2.16
2.16.1
2.16.2
2.16.3
2.16.4
2.17
A batch version
3
3.1
3.1.1
3.1.2
3.1.3
3.1.4
Variable lists
Specifying the estimation sample
Weights
Options
3.1.5
Header
Estimates and standard errors
Confidence intervals
3.1.6
3.1.7
3.1.8
3.1.9
Options for types of coefficients
Options for mlogit, mprobit, and slogit
Other options
Standardized coefficients
Factor and percent change
3.2
3.3
3.3.1 Wald
The accumulate option
3.3.2
Avoiding invalid LR tests
3.4
3.5
Syntax of fitstat
Options
Models and measures
Example of fitstat
Methods and formulas for fitstat
3.6
3.6.1
3.6.2
3.6.3
Specifying the levels of variables
Options controlling output
3.6.4
Options
Options for confidence intervals
Options used for bootstrapped confidence intervals
3.6.5
Options
3.6.6
Options
3.6.7
Options
Options for confidence intervals and marginals
Variables generated
3.6.8
3.7
3.8
II
4
4.1
4.1.1
4.1.2
4.2
Variable lists
Specifying the estimation sample
Weights
Options
Example
4.2.1
4.3
4.3.1
One- and two-tailed tests
Testing single coefficients using test
Testing single coefficients using Irtest
4.3.2
Testing multiple coefficients using test
Testing multiple coefficients using Irtest
4.3.3
4.4
4.4.1
Example
4.4.2
4.4.3
Syntax
Options
Options controlling the list of values
4.5
4.5.1
4.5.2
4.6
4.6.1
4.6.2
4.6.3
4.6.4
4.6.5
4.6.6
Marginal change
Discrete change
4.7
Multiplicative coefficients
Effect of the base probability
Percent change in the odds
4.8
5
5.1
5.1.1
5.1.2
5.2
Variable lists
Specifying the estimation sample
Weights
Options
5.2.1
5.2.2
5.3
5.3.1
5.3.2
5.4
5.5
5.6
5.7
5.8
5.8.1
5.8.2
5.8.3
5.8.4
5.8.5
5.8.6
5.8.7
Marginal change with prchange
Marginal change with mfx
Discrete change with prchange
Confidence intervals for discrete changes
Computing discrete change for a 10-year increase in age
5.8.8
5.9
5.9.1
5.9.2
5.9.3
6
6.1
6.1.1
6.2
Variable
Specifying the estimation sample
Weights
Options
6.2.1
6.2.2
6.2.3
6.3
6.3.1
Options
6.3.2
A likelihood-ratio test
A Wald test
Testing multiple independent variables
6.3.3
A Wald test for combining alternatives
Using test [category]*
An LR test for combining alternatives
Using constraint with lrtest*
6.4
Hausman test of IIA
Small-Hsiao test of IIA
6.5
6.6
6.6.1
6.6.2
Using predict to compare mlogit and ologit
6.6.3
6.6.4
6.6.5
Plotting probabilities for one outcome and two groups
Graphing probabilities for all outcomes for one group
6.6.6
Computing marginal and discrete change with prchange
Marginal change with mfx
6.6.7
6.6.8
Listing odds ratios with listcoef
Plotting odds ratios
6.6.9
6.6.10
Options for using matrices with mlogplot
Global macros and matrices used by mlogplot
Example
6.7
6.8
6.8.1
6.8.2
Options
Example
6.8.3
6.8.4
6.8.5
6.8.6
Higher-dimension
7
7.1
7.1.1
7.2
7.2.1
Example of the clogit model
7.2.2
7.2.3
Using predict
Using asprvalue
7.2.4
Setting up the data with case2alt
Fitting multinomial logit with clogit
7.2.5
Example of a mixed model
Interpretation of odds ratios using listcoef
Interpretation of predicted probabilities using asprvalue
Allowing the effects of alternative-specific variables to vary
over the alternatives
7.3
7.3.1
7.3.2
7.3.3
Options
Examples
7.3.4
7.4
7.4.1
Using predict
Using asprvalue
7.4.2
7.4.3
7.4.4
7.5
7.5.1
Options
Example of the rank-ordered logit model
7.5.2
Interpretation using odds ratios
Interpretation using predicted probabilities
7.6
8
8.1
8.1.1
8.1.2
Syntax
Options
Variables generated
8.1.3
8.2
8.2.1
Variable lists
Specifying the estimation sample
Weights
Options
8.2.2
8.2.3
Factor change in E(y | x)
Percent change in E(y | x)
Example of factor and percent change
Marginal change in E(y | x)
Example of marginal change using prchange
Example of marginal change using mfx
Discrete change in E(y | x)
Example of discrete change using prchange
Example of discrete change with confidence intervals
8.2.4
Example of predicted probabilities using prvalue
Example of predicted probabilities using prgen
Example of predicted probabilities using prcounts
8.2.5
8.3
8.3.1
NB1 and NB2 variance functions
8.3.2
Comparing the
8.3.3
8.3.4
8.3.5
8.4
8.4.1
8.4.2
8.4.3
8.4.4
8.4.5
tion sample
8.5
8.5.1
8.5.2
8.6
8.6.1
Variable lists
Options
8.6.2
8.6.3
8.6.4
Predicted probabilities with prvalue
Confidence intervals with prvalue
Predicted probabilities with prgen
8.7
8.7.1
8.7.2
LR tests of
Vuong test of nonnested models
8.8
9
9.1
9.1.1
variables
9.1.2
variables
9.1.3
Testing the effect of membership in one category versus the
reference category
Testing the effect of membership in two nonreference categories
Testing that a categorical independent variable has no effect
Testing whether treating an ordinal variable as interval loses
information
9.1.4
Computing discrete change with prchange
Computing discrete change with prvalue
9.2
9.2.1
9.2.2 Computing sex
9.3
9.3.1
9.3.2
9.4
Options
9.4.1
9.4.2
9.4.3
9.4.4
9.4.5
9.4.6
9.4.7
9.5
9.6
9.6.1
9.6.2
9.6.3
9.6.4
9.7
A Syntax for SPost commands
A.I asprvalue
Syntax
Description
Options
Examples
A.2 brant
Syntax
Description
Option............................... 452
Examples
Saved results
A.3 case2alt
Syntax
Description
Options
Example
A.4 countfit
Syntax
Description
Options for specifying the model
Options to select the models to fit
Options to label and save results
Options to control what is printed
Example
A.5 fitstat
Syntax
Description
Options
Examples
Saved results
A.6 leastlikely
Syntax
Description
Options
Options for listing
Examples
A.7 listcoef
Syntax
Description
Options
Options for nominal
Examples
Saved results............................
Α.
Syntax
Options
Example
A.9 mlogplot
Syntax
Description
Options
Examples
A.10 mlogtest
Syntax
Description
Options
Examples
Saved results............................
Acknowledgment
Α.
Syntax
Description
Dialog box controls
A.
Syntax
Examples
A.
Syntax
Description
Options
Examples
Variables
A.
Syntax
Description
Options
Examples
A.
Syntax
Description
Options
Variables
Examples
A.16 prgen
Syntax
Description
Options
Options
Examples
Variables
A.17 prtab
Syntax
Description
Options
Examples
A.18 prvame
Syntax
Description
Options
Options for confidence intervais
Options
Examples
Saved results............................
A.19
Syntax
Description
Options
Examples
B
B.I binlfp2
B.2 couart2
B.3 gsskidvalue2
B.4 nomocc2
B.5 ordwarm2
B.6 science2
B.7 travel2
B.8 wlsrnk
References
Author index
Subject index
The goal
Second Edition, is to make it easier to carry out the computations necessary for the
full interpretation of regression models for categorical outcomes using
interpretation of these models is made more complex because the models are nonlinear.
Most software packages that estimate these models do not provide options that make
it simple to compute the quantities that are useful for interpretation. In this book, the
authors briefly describe the statistical issues involved in interpretation, and then they
show how you can use
|
| adam_txt |
Contents
Preface
I General Information
1
1.1
1.2
1.3
1.4
1.5
1.5.1
1.5.2
Installing SPost using search
Installing SPost using net install
1.5.3
1.5.4
1.5.5
1.5.6
1.6
2
2.1
Changing the scrollback buffer size
Changing the display of variable names in the Variables window
2.2
2.3
2.3.1
2.3.2
2.3.3
2.4
2.5
2.6
Options
2.6.1
2.6.2
2.6.3
2.7
2.7.1
2.7.2
2.7.3
2.8
2.9
2.9.1
2.9.2
2.9.3
2.9.4
Using Stata's Do-file Editor
Using other editors to create do-files
2.9.5
2.10
2.11
2.11.1
2.11.2
2.11.3
Examples of if qualifier
2.11.4
2.12
2.12.1
2.12.2
2.12.3
2.12.4
2.12.5
2.13
2.13.1
2.13.2
2.13.3
2.13.4
Breaking a categorical variable into a set of binary variables
More examples of creating binary variables
Nonlinear transformations
Interaction terms
2.14
2.14.1
2.14.2
2.14.3
2.15
2.16
2.16.1
2.16.2
2.16.3
2.16.4
2.17
A batch version
3
3.1
3.1.1
3.1.2
3.1.3
3.1.4
Variable lists
Specifying the estimation sample
Weights
Options
3.1.5
Header
Estimates and standard errors
Confidence intervals
3.1.6
3.1.7
3.1.8
3.1.9
Options for types of coefficients
Options for mlogit, mprobit, and slogit
Other options
Standardized coefficients
Factor and percent change
3.2
3.3
3.3.1 Wald
The accumulate option
3.3.2
Avoiding invalid LR tests
3.4
3.5
Syntax of fitstat
Options
Models and measures
Example of fitstat
Methods and formulas for fitstat
3.6
3.6.1
3.6.2
3.6.3
Specifying the levels of variables
Options controlling output
3.6.4
Options
Options for confidence intervals
Options used for bootstrapped confidence intervals
3.6.5
Options
3.6.6
Options
3.6.7
Options
Options for confidence intervals and marginals
Variables generated
3.6.8
3.7
3.8
II
4
4.1
4.1.1
4.1.2
4.2
Variable lists
Specifying the estimation sample
Weights
Options
Example
4.2.1
4.3
4.3.1
One- and two-tailed tests
Testing single coefficients using test
Testing single coefficients using Irtest
4.3.2
Testing multiple coefficients using test
Testing multiple coefficients using Irtest
4.3.3
4.4
4.4.1
Example
4.4.2
4.4.3
Syntax
Options
Options controlling the list of values
4.5
4.5.1
4.5.2
4.6
4.6.1
4.6.2
4.6.3
4.6.4
4.6.5
4.6.6
Marginal change
Discrete change
4.7
Multiplicative coefficients
Effect of the base probability
Percent change in the odds
4.8
5
5.1
5.1.1
5.1.2
5.2
Variable lists
Specifying the estimation sample
Weights
Options
5.2.1
5.2.2
5.3
5.3.1
5.3.2
5.4
5.5
5.6
5.7
5.8
5.8.1
5.8.2
5.8.3
5.8.4
5.8.5
5.8.6
5.8.7
Marginal change with prchange
Marginal change with mfx
Discrete change with prchange
Confidence intervals for discrete changes
Computing discrete change for a 10-year increase in age
5.8.8
5.9
5.9.1
5.9.2
5.9.3
6
6.1
6.1.1
6.2
Variable
Specifying the estimation sample
Weights
Options
6.2.1
6.2.2
6.2.3
6.3
6.3.1
Options
6.3.2
A likelihood-ratio test
A Wald test
Testing multiple independent variables
6.3.3
A Wald test for combining alternatives
Using test [category]*
An LR test for combining alternatives
Using constraint with lrtest*
6.4
Hausman test of IIA
Small-Hsiao test of IIA
6.5
6.6
6.6.1
6.6.2
Using predict to compare mlogit and ologit
6.6.3
6.6.4
6.6.5
Plotting probabilities for one outcome and two groups
Graphing probabilities for all outcomes for one group
6.6.6
Computing marginal and discrete change with prchange
Marginal change with mfx
6.6.7
6.6.8
Listing odds ratios with listcoef
Plotting odds ratios
6.6.9
6.6.10
Options for using matrices with mlogplot
Global macros and matrices used by mlogplot
Example
6.7
6.8
6.8.1
6.8.2
Options
Example
6.8.3
6.8.4
6.8.5
6.8.6
Higher-dimension
7
7.1
7.1.1
7.2
7.2.1
Example of the clogit model
7.2.2
7.2.3
Using predict
Using asprvalue
7.2.4
Setting up the data with case2alt
Fitting multinomial logit with clogit
7.2.5
Example of a mixed model
Interpretation of odds ratios using listcoef
Interpretation of predicted probabilities using asprvalue
Allowing the effects of alternative-specific variables to vary
over the alternatives
7.3
7.3.1
7.3.2
7.3.3
Options
Examples
7.3.4
7.4
7.4.1
Using predict
Using asprvalue
7.4.2
7.4.3
7.4.4
7.5
7.5.1
Options
Example of the rank-ordered logit model
7.5.2
Interpretation using odds ratios
Interpretation using predicted probabilities
7.6
8
8.1
8.1.1
8.1.2
Syntax
Options
Variables generated
8.1.3
8.2
8.2.1
Variable lists
Specifying the estimation sample
Weights
Options
8.2.2
8.2.3
Factor change in E(y | x)
Percent change in E(y | x)
Example of factor and percent change
Marginal change in E(y | x)
Example of marginal change using prchange
Example of marginal change using mfx
Discrete change in E(y | x)
Example of discrete change using prchange
Example of discrete change with confidence intervals
8.2.4
Example of predicted probabilities using prvalue
Example of predicted probabilities using prgen
Example of predicted probabilities using prcounts
8.2.5
8.3
8.3.1
NB1 and NB2 variance functions
8.3.2
Comparing the
8.3.3
8.3.4
8.3.5
8.4
8.4.1
8.4.2
8.4.3
8.4.4
8.4.5
tion sample
8.5
8.5.1
8.5.2
8.6
8.6.1
Variable lists
Options
8.6.2
8.6.3
8.6.4
Predicted probabilities with prvalue
Confidence intervals with prvalue
Predicted probabilities with prgen
8.7
8.7.1
8.7.2
LR tests of
Vuong test of nonnested models
8.8
9
9.1
9.1.1
variables
9.1.2
variables
9.1.3
Testing the effect of membership in one category versus the
reference category
Testing the effect of membership in two nonreference categories
Testing that a categorical independent variable has no effect
Testing whether treating an ordinal variable as interval loses
information
9.1.4
Computing discrete change with prchange
Computing discrete change with prvalue
9.2
9.2.1
9.2.2 Computing sex
9.3
9.3.1
9.3.2
9.4
Options
9.4.1
9.4.2
9.4.3
9.4.4
9.4.5
9.4.6
9.4.7
9.5
9.6
9.6.1
9.6.2
9.6.3
9.6.4
9.7
A Syntax for SPost commands
A.I asprvalue
Syntax
Description
Options
Examples
A.2 brant
Syntax
Description
Option. 452
Examples
Saved results
A.3 case2alt
Syntax
Description
Options
Example
A.4 countfit
Syntax
Description
Options for specifying the model
Options to select the models to fit
Options to label and save results
Options to control what is printed
Example
A.5 fitstat
Syntax
Description
Options
Examples
Saved results
A.6 leastlikely
Syntax
Description
Options
Options for listing
Examples
A.7 listcoef
Syntax
Description
Options
Options for nominal
Examples
Saved results.
Α.
Syntax
Options
Example
A.9 mlogplot
Syntax
Description
Options
Examples
A.10 mlogtest
Syntax
Description
Options
Examples
Saved results.
Acknowledgment
Α.
Syntax
Description
Dialog box controls
A.
Syntax
Examples
A.
Syntax
Description
Options
Examples
Variables
A.
Syntax
Description
Options
Examples
A.
Syntax
Description
Options
Variables
Examples
A.16 prgen
Syntax
Description
Options
Options
Examples
Variables
A.17 prtab
Syntax
Description
Options
Examples
A.18 prvame
Syntax
Description
Options
Options for confidence intervais
Options
Examples
Saved results.
A.19
Syntax
Description
Options
Examples
B
B.I binlfp2
B.2 couart2
B.3 gsskidvalue2
B.4 nomocc2
B.5 ordwarm2
B.6 science2
B.7 travel2
B.8 wlsrnk
References
Author index
Subject index
The goal
Second Edition, is to make it easier to carry out the computations necessary for the
full interpretation of regression models for categorical outcomes using
interpretation of these models is made more complex because the models are nonlinear.
Most software packages that estimate these models do not provide options that make
it simple to compute the quantities that are useful for interpretation. In this book, the
authors briefly describe the statistical issues involved in interpretation, and then they
show how you can use |
| any_adam_object | 1 |
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| author | Long, J. Scott Freese, Jeremy |
| author_GND | (DE-588)171773071 (DE-588)1017211698 |
| author_facet | Long, J. Scott Freese, Jeremy |
| author_role | aut aut |
| author_sort | Long, J. Scott |
| author_variant | j s l js jsl j f jf |
| building | Verbundindex |
| bvnumber | BV021516874 |
| callnumber-first | Q - Science |
| callnumber-label | QA278 |
| callnumber-raw | QA278.2 |
| callnumber-search | QA278.2 |
| callnumber-sort | QA 3278.2 |
| callnumber-subject | QA - Mathematics |
| classification_rvk | MB 2520 MR 2200 QH 234 SK 840 ST 601 |
| classification_tum | DAT 307f SOZ 720 MAT 628f |
| ctrlnum | (OCoLC)255541289 (DE-599)BVBBV021516874 |
| discipline | Informatik Politologie Soziologie Mathematik Wirtschaftswissenschaften |
| discipline_str_mv | Informatik Politologie Soziologie Mathematik Wirtschaftswissenschaften |
| edition | 2. ed. |
| format | Book |
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| id | DE-604.BV021516874 |
| illustrated | Illustrated |
| index_date | 2024-07-02T14:21:10Z |
| indexdate | 2024-07-09T20:37:37Z |
| institution | BVB |
| isbn | 9781597180115 1597180114 |
| language | English |
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| oclc_num | 255541289 |
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| physical | XXXII, 527 S. Ill., graph. Darst. |
| publishDate | 2006 |
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| publisher | Stata Press |
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| series2 | A Stata Press publication |
| spelling | Long, J. Scott Verfasser (DE-588)171773071 aut Regression models for categorical dependent variables using Stata J. Scott Long ; Jeremy Freese 2. ed. College Station, Tex. Stata Press 2006 XXXII, 527 S. Ill., graph. Darst. txt rdacontent n rdamedia nc rdacarrier A Stata Press publication Analisi della regressione - statistica sbt Lehrbuch / Textbook - 28 Regression / Schätztheorie / PC-Software / Programmiersprache / Theorie Regressionsanalyse - Stata Stata - analisi della regressione sbt Statistik Mathematical statistics Regression analysis Stata (Computer programs) Statistics Stata (DE-588)4617285-3 gnd rswk-swf Regressionsanalyse (DE-588)4129903-6 gnd rswk-swf Regressionsanalyse (DE-588)4129903-6 s Stata (DE-588)4617285-3 s DE-604 Freese, Jeremy Verfasser (DE-588)1017211698 aut Digitalisierung UB Passau application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=014733419&sequence=000003&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis Digitalisierung UB Passau application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=014733419&sequence=000004&line_number=0002&func_code=DB_RECORDS&service_type=MEDIA Klappentext |
| spellingShingle | Long, J. Scott Freese, Jeremy Regression models for categorical dependent variables using Stata Analisi della regressione - statistica sbt Lehrbuch / Textbook - 28 Regression / Schätztheorie / PC-Software / Programmiersprache / Theorie Regressionsanalyse - Stata Stata - analisi della regressione sbt Statistik Mathematical statistics Regression analysis Stata (Computer programs) Statistics Stata (DE-588)4617285-3 gnd Regressionsanalyse (DE-588)4129903-6 gnd |
| subject_GND | (DE-588)4617285-3 (DE-588)4129903-6 |
| title | Regression models for categorical dependent variables using Stata |
| title_auth | Regression models for categorical dependent variables using Stata |
| title_exact_search | Regression models for categorical dependent variables using Stata |
| title_exact_search_txtP | Regression models for categorical dependent variables using Stata |
| title_full | Regression models for categorical dependent variables using Stata J. Scott Long ; Jeremy Freese |
| title_fullStr | Regression models for categorical dependent variables using Stata J. Scott Long ; Jeremy Freese |
| title_full_unstemmed | Regression models for categorical dependent variables using Stata J. Scott Long ; Jeremy Freese |
| title_short | Regression models for categorical dependent variables using Stata |
| title_sort | regression models for categorical dependent variables using stata |
| topic | Analisi della regressione - statistica sbt Lehrbuch / Textbook - 28 Regression / Schätztheorie / PC-Software / Programmiersprache / Theorie Regressionsanalyse - Stata Stata - analisi della regressione sbt Statistik Mathematical statistics Regression analysis Stata (Computer programs) Statistics Stata (DE-588)4617285-3 gnd Regressionsanalyse (DE-588)4129903-6 gnd |
| topic_facet | Analisi della regressione - statistica Lehrbuch / Textbook - 28 Regression / Schätztheorie / PC-Software / Programmiersprache / Theorie Regressionsanalyse - Stata Stata - analisi della regressione Statistik Mathematical statistics Regression analysis Stata (Computer programs) Statistics Stata Regressionsanalyse |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=014733419&sequence=000003&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=014733419&sequence=000004&line_number=0002&func_code=DB_RECORDS&service_type=MEDIA |
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