now what do i do with this function
play

Now what do I do with this function? Enrique Pinzn StataCorp LP - PowerPoint PPT Presentation

Jan 13, 2023 •168 likes •841 views

Now what do I do with this function? Enrique Pinzn StataCorp LP October 19, 2017 Madrid (StataCorp LP) October 19, 2017 Madrid 1 / 42 Initial thoughts Nonparametric regression and about effects/questions npregress Mean relation between

  1. Now what do I do with this function? Enrique Pinzón StataCorp LP October 19, 2017 Madrid (StataCorp LP) October 19, 2017 Madrid 1 / 42

  2. Initial thoughts Nonparametric regression and about effects/questions npregress Mean relation between an outcome and covariates ◮ Model birtweight : age, education level, smoked, number of prenatal visits, ... ◮ Model wages: age, education level, profession, tenure, ... ◮ E ( y | X ) , conditional mean Parametric models have a known functional form Linear regression: E ( y | X ) = X β E ( y | X ) = F ( X β ) Binary: Poisson: E ( y | X ) = exp ( X β ) Nonparametric E ( y | X ) . The result of using predict (StataCorp LP) October 19, 2017 Madrid 2 / 42

  3. Initial thoughts Nonparametric regression and about effects/questions npregress Mean relation between an outcome and covariates ◮ Model birtweight : age, education level, smoked, number of prenatal visits, ... ◮ Model wages: age, education level, profession, tenure, ... ◮ E ( y | X ) , conditional mean Parametric models have a known functional form Linear regression: E ( y | X ) = X β E ( y | X ) = F ( X β ) Binary: Poisson: E ( y | X ) = exp ( X β ) Nonparametric E ( y | X ) . The result of using predict (StataCorp LP) October 19, 2017 Madrid 2 / 42

  4. Initial thoughts Nonparametric regression and about effects/questions npregress Mean relation between an outcome and covariates ◮ Model birtweight : age, education level, smoked, number of prenatal visits, ... ◮ Model wages: age, education level, profession, tenure, ... ◮ E ( y | X ) , conditional mean Parametric models have a known functional form Linear regression: E ( y | X ) = X β E ( y | X ) = F ( X β ) Binary: Poisson: E ( y | X ) = exp ( X β ) Nonparametric E ( y | X ) . The result of using predict (StataCorp LP) October 19, 2017 Madrid 2 / 42

  5. Initial thoughts Nonparametric regression and about effects/questions npregress Mean relation between an outcome and covariates ◮ Model birtweight : age, education level, smoked, number of prenatal visits, ... ◮ Model wages: age, education level, profession, tenure, ... ◮ E ( y | X ) , conditional mean Parametric models have a known functional form Linear regression: E ( y | X ) = X β E ( y | X ) = F ( X β ) Binary: Poisson: E ( y | X ) = exp ( X β ) Nonparametric E ( y | X ) . The result of using predict (StataCorp LP) October 19, 2017 Madrid 2 / 42

  6. Initial thoughts Nonparametric regression and about effects/questions npregress Mean relation between an outcome and covariates ◮ Model birtweight : age, education level, smoked, number of prenatal visits, ... ◮ Model wages: age, education level, profession, tenure, ... ◮ E ( y | X ) , conditional mean Parametric models have a known functional form Linear regression: E ( y | X ) = X β E ( y | X ) = F ( X β ) Binary: Poisson: E ( y | X ) = exp ( X β ) Nonparametric E ( y | X ) . The result of using predict (StataCorp LP) October 19, 2017 Madrid 2 / 42

  7. Initial thoughts Nonparametric regression and about effects/questions npregress Mean relation between an outcome and covariates ◮ Model birtweight : age, education level, smoked, number of prenatal visits, ... ◮ Model wages: age, education level, profession, tenure, ... ◮ E ( y | X ) , conditional mean Parametric models have a known functional form Linear regression: E ( y | X ) = X β E ( y | X ) = F ( X β ) Binary: Poisson: E ( y | X ) = exp ( X β ) Nonparametric E ( y | X ) . The result of using predict (StataCorp LP) October 19, 2017 Madrid 2 / 42

  8. (StataCorp LP) October 19, 2017 Madrid 3 / 42

  9. But ... We had nonparametric regression tools lpoly lowess (StataCorp LP) October 19, 2017 Madrid 4 / 42

  10. But ... We had nonparametric regression tools lpoly lowess (StataCorp LP) October 19, 2017 Madrid 4 / 42

  11. What happened in the past lpoly bweight mage if (msmoke==0 & medu>12 & fedu>12), /// mcolor(%30) lineopts(lwidth(thick)) (StataCorp LP) October 19, 2017 Madrid 5 / 42

  12. Effects: A thought experiment I give you the true function . list y x a gx in 1/10, noobs y x a gx 13.46181 .7630615 2 12.73349 1.41086 .9241793 1 1.547555 22.88834 1.816095 2 21.43813 10.97789 .8206556 2 13.01466 11.37173 .0440157 2 10.13213 -.1938587 1.083093 1 .439635 55.87413 3.32037 2 56.56772 2.94979 .8900821 1 1.804343 -1.178733 -2.342678 0 -2.856946 48.79958 3.418333 0 49.94323 (StataCorp LP) October 19, 2017 Madrid 6 / 42

  13. Effects: A thought experiment I give you the true function . list y x a gx in 1/10, noobs y x a gx 13.46181 .7630615 2 12.73349 1.41086 .9241793 1 1.547555 22.88834 1.816095 2 21.43813 10.97789 .8206556 2 13.01466 11.37173 .0440157 2 10.13213 -.1938587 1.083093 1 .439635 55.87413 3.32037 2 56.56772 2.94979 .8900821 1 1.804343 -1.178733 -2.342678 0 -2.856946 48.79958 3.418333 0 49.94323 (StataCorp LP) October 19, 2017 Madrid 6 / 42

  14. Effects: A thought experiment I give you the true function Do we know what are the marginal effects Do we know causal/treatment effects Do we know counterfactuals It seems cosmetic We cannot use margins (StataCorp LP) October 19, 2017 Madrid 7 / 42

  15. Effects: A thought experiment I give you the true function Do we know what are the marginal effects Do we know causal/treatment effects Do we know counterfactuals It seems cosmetic We cannot use margins (StataCorp LP) October 19, 2017 Madrid 7 / 42

  16. Effects: A thought experiment I give you the true function Do we know what are the marginal effects Do we know causal/treatment effects Do we know counterfactuals It seems cosmetic We cannot use margins (StataCorp LP) October 19, 2017 Madrid 7 / 42

  17. Effects: A thought experiment I give you the true function Do we know what are the marginal effects Do we know causal/treatment effects Do we know counterfactuals It seems cosmetic We cannot use margins (StataCorp LP) October 19, 2017 Madrid 7 / 42

  18. A detour margins (StataCorp LP) October 19, 2017 Madrid 8 / 42

  19. Effects: outcome of interest (StataCorp LP) October 19, 2017 Madrid 9 / 42

  20. Data crash 1 if crash traffic Measure of vehicular traffic tickets Number of traffic tickets male 1 if male (StataCorp LP) October 19, 2017 Madrid 10 / 42

  21. Probit model and average marginal effects probit crash tickets traffic i.male . margins Predictive margins Number of obs = 948 Model VCE : OIM Expression : Pr(crash), predict() Delta-method Margin Std. Err. z P>|z| [95% Conf. Interval] _cons .1626529 .0044459 36.58 0.000 .153939 .1713668 . margins, dydx(traffic tickets) Average marginal effects Number of obs = 948 Model VCE : OIM Expression : Pr(crash), predict() dy/dx w.r.t. : tickets traffic Delta-method dy/dx Std. Err. z P>|z| [95% Conf. Interval] tickets .0857818 .0031049 27.63 0.000 .0796963 .0918672 traffic .0055371 .0020469 2.71 0.007 .0015251 .009549 (StataCorp LP) October 19, 2017 Madrid 11 / 42

  22. Probit model and average marginal effects probit crash tickets traffic i.male . margins Predictive margins Number of obs = 948 Model VCE : OIM Expression : Pr(crash), predict() Delta-method Margin Std. Err. z P>|z| [95% Conf. Interval] _cons .1626529 .0044459 36.58 0.000 .153939 .1713668 . margins, dydx(traffic tickets) Average marginal effects Number of obs = 948 Model VCE : OIM Expression : Pr(crash), predict() dy/dx w.r.t. : tickets traffic Delta-method dy/dx Std. Err. z P>|z| [95% Conf. Interval] tickets .0857818 .0031049 27.63 0.000 .0796963 .0918672 traffic .0055371 .0020469 2.71 0.007 .0015251 .009549 (StataCorp LP) October 19, 2017 Madrid 11 / 42

  23. Probit model and average marginal effects probit crash tickets traffic i.male . margins Predictive margins Number of obs = 948 Model VCE : OIM Expression : Pr(crash), predict() Delta-method Margin Std. Err. z P>|z| [95% Conf. Interval] _cons .1626529 .0044459 36.58 0.000 .153939 .1713668 . margins, dydx(traffic tickets) Average marginal effects Number of obs = 948 Model VCE : OIM Expression : Pr(crash), predict() dy/dx w.r.t. : tickets traffic Delta-method dy/dx Std. Err. z P>|z| [95% Conf. Interval] tickets .0857818 .0031049 27.63 0.000 .0796963 .0918672 traffic .0055371 .0020469 2.71 0.007 .0015251 .009549 (StataCorp LP) October 19, 2017 Madrid 11 / 42

  24. Not calculus . margins, at(traffic=generate(traffic*1.10)) at(traffic=generate(traffic)) /// > contrast(atcontrast(r) nowald) Contrasts of predictive margins Model VCE : OIM Expression : Pr(crash), predict() 1._at : traffic = traffic*1.10 2._at : traffic = traffic Delta-method Contrast Std. Err. [95% Conf. Interval] _at (2 vs 1) -.0028589 .0010882 -.0049917 -.0007262 (StataCorp LP) October 19, 2017 Madrid 12 / 42

Recommend

Function Calls Function Calls Python supports expressions with math-like functions A

Function Calls Function Calls Python supports expressions with math-like functions A

Module 3 Function Calls Function Calls Python supports expressions with math-like functions A function in an expression is a function call Function calls have the form name (x,y,) function argument name Arguments are

333 views • 20 slides
The Glue Function different properties An Example of How Mathematicians Think Introducing...

The Glue Function different properties An Example of How Mathematicians Think Introducing...

The Glue Function Niko Schultz Function and sequence: The Glue Function different properties An Example of How Mathematicians Think Introducing... the glue function! Lets make our function Niko Schultz smooth September 5, 2014

463 views • 17 slides
The Natural Logarithm Function and The Exponential Function One specific logarithm function is

The Natural Logarithm Function and The Exponential Function One specific logarithm function is

The Natural Logarithm Function and The Exponential Function One specific logarithm function is singled out and one particular exponential function is singled out. Definition e = lim x 0 (1 + x ) 1 / x Alan H. SteinUniversity of Connecticut

627 views • 29 slides
Functions Function Calls Python supports expressions with math-like functions A function

Functions Function Calls Python supports expressions with math-like functions A function

Mini-Lecture 4 Functions Function Calls Python supports expressions with math-like functions A function in an expression is a function call Will explain the meaning of this later Function expressions have the form fun (x,y,)

411 views • 15 slides
G-Protein Coupled Receptors: Structure and Function Structure and Function Dr. Rishi Somvanshi

G-Protein Coupled Receptors: Structure and Function Structure and Function Dr. Rishi Somvanshi

PCTH 400 G-Protein Coupled Receptors: Structure and Function Structure and Function Dr. Rishi Somvanshi 2405 Wesbrook Mall rishiks@mail.ubc.ca 604-827-3672 Learning Objectives 1. GPCR ? Structure and Synthesis 2. Function ?

395 views • 28 slides
Function Representation & Spherical Harmonics Function approximation G (x) ... function

Function Representation & Spherical Harmonics Function approximation G (x) ... function

Function Representation & Spherical Harmonics Function approximation G (x) ... function to represent B 1 (x), B 2 (x), B n (x) basis functions G (x) is a linear combination of basis functions n = G ( x ) c B

540 views • 23 slides
Recursion What happens when a function calls itself? This is known as a recursive function

Recursion What happens when a function calls itself? This is known as a recursive function

Recursion What happens when a function calls itself? This is known as a recursive function Recursion What happens when a function calls itself? This is known as a recursive function Every function call is added to the stack

482 views • 19 slides
Chapter 13 Recursion 1 Recursion A function that "calls itself" In function

Chapter 13 Recursion 1 Recursion A function that "calls itself" In function

Chapter 13 Recursion 1 Recursion A function that "calls itself" In function definition, call to same function Divide and Conquer Basic design technique Break large task into subtasks Use recursion when subtasks

461 views • 16 slides
(from Chapter 9 of the text 4 th or 5 th edition) Function Definitions Syntax and

(from Chapter 9 of the text 4 th or 5 th edition) Function Definitions Syntax and

IT350 Web and Internet Programming SlideSet #9: JavaScript Functions (from Chapter 9 of the text 4 th or 5 th edition) Function Definitions Syntax and terminology: function function-name ( parameter-list ) { declarations and statements }

272 views • 6 slides
Disclosures Contemporary Assessment of Cardiac I have nothing to disclose Function by

Disclosures Contemporary Assessment of Cardiac I have nothing to disclose Function by

12/17/16 Disclosures Contemporary Assessment of Cardiac I have nothing to disclose Function by Echocardiography Ann Bolger, MD William Watt Kerr Professor of Medicine Systolic function in the echo lab: LV function in context What is the

339 views • 11 slides
v1 v2 vn my-map : (define (my-map f xs) F F F (F v2) (F vn) (F v1) (if (null? xs) null

v1 v2 vn my-map : (define (my-map f xs) F F F (F v2) (F vn) (F v1) (if (null? xs) null

Higher-order List Func2ons Higher-Order List Functions A function is higher-order if it takes another in Racket function as an input and/or returns another function as a result. E.g. app-3-5 , make-linear-function , flip2 from the previous

519 views • 6 slides
v1 v2 vn (if (null? xs) null F F F (cons ( f (first xs)) (F vn) (F v2) (F v1) (my-map f

v1 v2 vn (if (null? xs) null F F F (cons ( f (first xs)) (F vn) (F v2) (F v1) (my-map f

Higher-order List Func2ons Higher-Order List Functions A function is higher-order if it takes another in Racket function as an input and/or returns another function as a result. E.g. app-3-5 , make-linear-function , flip2 . We will now study

300 views • 6 slides
What is executive function? There are many brain-based abilities that make up executive

What is executive function? There are many brain-based abilities that make up executive

10/27/2014 Executive Function MAKING THE WORLD A BIT EASIER TO NAVIGATE: USING EXECUTIVE FUNCTION SKILLS Brenda Smith Myles, Ph.D. brenda_myles@mac.com Executive Function The set of brain-based abilities that help people control their

617 views • 39 slides
2 Unit Bridging Course Day 10 Circular Functions III The cosine function, identities and

2 Unit Bridging Course Day 10 Circular Functions III The cosine function, identities and

2 Unit Bridging Course Day 10 Circular Functions III The cosine function, identities and derivatives Clinton Boys 1 / 31 The cosine function The cosine function, abbreviated to cos, is very similar to the sine function. In fact, the

347 views • 31 slides
Value function and optimal trajectories for a control problem with supremum cost function and

Value function and optimal trajectories for a control problem with supremum cost function and

Value function and optimal trajectories for a control problem with supremum cost function and state constraints Hasnaa Zidani ENSTA ParisTech, University of Paris-Saclay joint work with: A. Assellaou, & O. Bokanowski, & A. Desilles

448 views • 41 slides
Viruses X-ray, EM structure function structure function properties thermal stability

Viruses X-ray, EM structure function structure function properties thermal stability

Viruses X-ray, EM structure function structure function properties thermal stability mechanics electrostatics vibrations Etc PHYSICAL VIROLOGY Single molecule techniques provide complementary information to structural

918 views • 65 slides
Registers and Stack Frames Lecture 6 Function calls and stack frames function invocation

Registers and Stack Frames Lecture 6 Function calls and stack frames function invocation

Registers and Stack Frames Lecture 6 Function calls and stack frames function invocation contexts are strictly nested stack mechanism is adequate for managing parameters and locals Information needed for function calls arguments

577 views • 14 slides
Learning From Data Lecture 6 Bounding The Growth Function Bounding the Growth Function Models

Learning From Data Lecture 6 Bounding The Growth Function Bounding the Growth Function Models

Learning From Data Lecture 6 Bounding The Growth Function Bounding the Growth Function Models are either Good or Bad The VC Bound - replacing |H| with m H ( N ) M. Magdon-Ismail CSCI 4100/6100 recap: The Growth Function m H ( N ) A new

316 views • 31 slides
Vector Functions A vector function is simply a function whose codomain is R n . In other words,

Vector Functions A vector function is simply a function whose codomain is R n . In other words,

Vector Functions A vector function is simply a function whose codomain is R n . In other words, rather than taking on real values, it takeson vector values. We will often use the notation x = x ( t ) to denote a vector function. Note: The text

522 views • 4 slides
Function Points What is Function Point Analysis? Approach to estimating SW size, which is

Function Points What is Function Point Analysis? Approach to estimating SW size, which is

Function Points What is Function Point Analysis? Approach to estimating SW size, which is independent of language development methodology technology capability of the project team hardness of the problem

630 views • 21 slides
decrements in GFR largely correlates to the deterioration and other kidney function including

decrements in GFR largely correlates to the deterioration and other kidney function including

is a physiological property determine function of all single nephrons taken together decrements in GFR largely correlates to the deterioration and other kidney function including hormonal production and metabolic function Diet and

859 views • 41 slides
Correlation function and response function in shell model of turbulence T. Ooshida, M. Otsuki 1 ,

Correlation function and response function in shell model of turbulence T. Ooshida, M. Otsuki 1 ,

Nonequilibrium Dynamics in Astrophysics and Material Science, 2011/11/2, Kyoto Univ. Correlation function and response function in shell model of turbulence T. Ooshida, M. Otsuki 1 , S. Goto 2 , A. Nakahara 3 , T. Matsumoto 4 Tottori U., Aoyama

450 views • 14 slides
Clin Endocrinol (Oxf). 2010 Jun;72(6):820-4. Epub 2009 Oct 15. Maternal thyroid function

Clin Endocrinol (Oxf). 2010 Jun;72(6):820-4. Epub 2009 Oct 15. Maternal thyroid function

Please note: Maternal thyroid function appears to be related to breech presentation at term, yet we do not understand how or why. Further research is needed to clarify that relationship between a mothers thyroid function and her babys fetal

263 views • 3 slides
Before we begin Any questions? Function Pointers Recall: Program Memory Function pointers

Before we begin Any questions? Function Pointers Recall: Program Memory Function pointers

Before we begin Any questions? Function Pointers Recall: Program Memory Function pointers The memory used by a program is generally Provides access to executable code section. separated into the following sections: Function

669 views • 7 slides

More recommend