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I found these books quite helpful. In particular, the book wastes no time in introducing mathematical notations to models, which I found intimidating at first; but later found that they were well explained. I liked the format of breaking down continuous dependent variables to one volume and leaving the remaining dependents variables to the second volume. The chapters on 3-level models were particularly e book includes lots of output and allows to "work along" with chapter beautiful easily. I only have two complaints about the book; both linked to the exercise sections. Firstly, some exercises were confusing. Most of these were fine, but I felt that each chapter had one/two exercises that contained vague questions that were not always relevant to the chapter. Secondly, worked examples are scarce. The majority of the exercises do not include a "worked example" or a set of solutions. Only two or three of the exercises per chapter include a set of solutions which could be found online. Although I had the possibility to try myself at the end of a chapter, I rarely had the opportunity to confirm whether I was on the right track or not. I found this a bit annoying. Overall, a amazing resource.

The first edition of Rabe-Hesketh and Skrondal's "Multilevel and Longitudinal ModelingUsing Stata" was published in 2005. The second edition was released in 2008, and now thisthird edition in 2012. With each edition the scope of the model's discussed in the texthas increased. This release is in fact a 2-volume work, with the first volume devoted topanel models having a continuous response (or dependent variable), and the second todiscrete response panel arly every panel model in the literature is addressed in the text. Discussion beginswith a review of primary linear regression and provides the basics upon which more complexmodels will be developed. Then variance-components are addressed, explaining concepts suchas between-subject heterogeneity and within-subject dependence. Following this the authorsintroduce fixed and random effects models, and then delve into the info of both randomintercept and random coefficient models. Mixed effects models is given a thorough llowing a discussion of subject-specific models, the authors turn to population-averagedor marginal models, as well as growth curve models. The first volume concludes with chaptersdevoted to higher-level models with nested random effects and crossed random effects roughout the volume each model, where appropriate, is approached as one, two, and higherlevel models.Volume two addresses one, two, and higher level categorical response models, count models,and survival or duration models. The emphasis, of course, is on understanding data thatis structured as panels - whether clustered or longitudinal. Zero-inflated count models,for example, are not discussed, nor are generalized binomial, generalized Poisson, orgeneralized negative binomial models. But near every type of categorical response panel modelis discussed -- in full.Volume one is over 500 pages in length; volume two is a bit shorter. Together the two volumesconsist of 974 pages plus nearly 40 Roman numeral pages. Stata statistical software is usedthroughout the text, which is dually published by Stata Press and Chapman & Hall/CRC. Stataand Limdep econometric software are in my opinion the two most compehensive panel-modelingstatistical packages available, with SAS the next best in this regard. Stata, as a generalpurpose stat pack has a much wider range of capabilities, as does SAS. It is therefore avery amazing choice of software to use for examining this class of models. It is also a comparativelyeasy programming language. The authors have written 'gllamm', a Stata command that allows estimationof a lot of of the more complex models disussed in the text, including, for example, athree-level random coefficient logistic regression model. Most examples though rely on Stata'sbuilt-in commands, plus it's Mata matrix programming is two-volume work is in my opinion the foremost text on multilevel uses Stata for examples, but any text that uses examples to explain difficult statisticalconcepts and methods needs to use some type of statistical software. Stata is ideal for thistype of modeling, so has been used in this text. Researchers who use other software formodeling; eg SAS, R, SPSS, etc, can use the methods taught in this volume with their preferredpackage, insofar as it has the capability to estimate a particular type of model.I highly recommend this two-volume set of books to anyone with an interest in modelingmultilevel and longitudial models, regardless of their preferred statistical software. It isthe most comprehensive work available on applied multilevel modeling. It is also very wellwritten, with each model examined in a very clear manner. Data sets and author-written code isprovided on the book's web site. Readers therefore are able to replicate the exmaples in the book,or to adapt them for their own projects.

**An Introduction to Statistics and Data ysis Using Stata®: From Research Design to Final Report**[] 2019-12-18 20:47

Beyond learning Stata (which I had never used), this book is even more valuable in the general research advice. So a lot of books forget to contain this in tandem with the statistical ysis, so the inclusion in this book is a very welcome addition. I use this as a reference when running stats in SPSS for my research. The book is also written in a no-nonsense layman language so it is very accessible to the common person. Highly recommended for researchers and people wanting to learn Stata.

**An Introduction to Statistics and Data ysis Using Stata®: From Research Design to Final Report**[] 2019-12-18 20:47

I now have about 12 of the most recently published STATA (and one MATA) books out there. I really appreciate the author's clear writing style and explanations around each section. Also the book uniquely provides how you would show a summary of the results of each technique to laypeople and then to statistical experts (peer reviews). The summary of when to use each type of statistical study, ysis, regression, etc. is also very nicely done. I would recommend this book and Mitchell's "A visual tutorial to STATA graphics" which is a must for STATA users.

**An Introduction to Statistics and Data ysis Using Stata®: From Research Design to Final Report**[] 2019-12-18 20:47

Very well organized, simple to understand and laid out so that it's not overwhelming. There's plenty of examples specifically for STRATA in the book, and code is blocked off in gray and very simple to read( and use).It is well written and presented in a very logical method that slowly builds on previous ere's a generous use of charts, diagram, and other visual learning aids that break the text this book up and hold it from being dry or boring.

**An Introduction to Statistics and Data ysis Using Stata®: From Research Design to Final Report**[] 2019-12-18 20:47

This book provides an perfect step-by-step introduction to statistics and Stata. It covers the basics of the research process, data collection, sampling, questionnaire design, and writing research (with a amazing overview of how to do research projects). There is a separate chapter on writing research papers, which rare in this kind of book. Notably, it also contains APA is book could be covered two semester stats course. Ideally, it would be used in an intermediate-advanced undergraduate course or a lower level graduate class. It addresses both methods and stats. It could be also used with a methods class doing a quantitative research project. Scholars might search it helpful for brushing e text addresses how various yses are used in various fields, descriptive stats, hypothesis testing, covers key topics, and expected tables. It was pleasantly surprising to see regression diagnostics, logit/probit, and regression ysis with categorical dependent variables e text uses clear straightforward language and contains no massive math review (which often turns people away). There are news articles pop outs, framed in the current context but also relying on media that students are likely to encounter regularly. Easy definitions are provided for complicated terminology, no sidebar boxes for definitions are necessary. There are a lot of subsections to thoroughly breakdown topics. Commands appear in bold throughout the text and in the index. Each chapter also contains a summary of commands. The book contains a glossary, name index, and topic index. There is also an appendix of stata commands.

**An Introduction to Statistics and Data ysis Using Stata®: From Research Design to Final Report**[] 2019-12-18 20:47

I am currently managing a research contract and it’s been so long since I have done research on my own that I realized as I was putting together some introductory materials for our vendors, that I had even forgotten some of the terminology. So, as you might imagine, this book was a introduces you to Stata and that in and of itself is very useful but it also has a lot of research advice. It talks about open-and close-ended questions to use in surveys and what kind of surveys you should use at various times. It reminds you about the basic, fundamental data sets like the General Social Survey, talks about distribution and regression. In short, this is a amazing book to have by your side when you are reviewing a research an absolute bonus, it is written in simple to understand, plain English. Something that very few books such as this can claim.I found it to be absolutely invaluable and highly recommend it.

**An Introduction to Statistics and Data ysis Using Stata®: From Research Design to Final Report**[] 2019-12-18 20:47

An Introduction to Statistics and Data ysis Using Stata®: From Research Design to Final Report is a useful book. I have been working in the field of statistical ysis for over 15 years now and like to hold up on fresh information and trends. This book delivers useful tip that applies in the true globe jobs and techniques. I found some fresh information in this book that has helped me already. This is a amazing book with perfect data about data ysis.

**Interaction Effects in Linear and Generalized Linear Models: Examples and Applications Using Stata (Advanced Quantitative Techniques in the Social Sciences Book 12)**[] 2020-6-25 18:34

Thank GOD I found this book. This book provide at first the primary understanding of interactions and slowly to advanced knowledge for OLS and GLM. It also provide an understanding and a practical tools which is the ICLAC to create researcher easier in ysing the interactions.

Joshua Angrist is The Man when it comes to using instrumental variables to figure out what is going on in matters of medical or educational research where randomized controls can't be used for ethical or practical reasons. This is The Book to go to. Why only four stars? I am out of the business now and was looking for a lighter read. If you are serious about this subject, this is the book for you.

I am a doctoral student and this book has been assigned as a part of an advanced stats course. After taking a lot of statistics courses over the years, I'd have to say that the econometrics in this book is not what I'd call "harmless". It gets beautiful intense beautiful quickly with equations which are not the easiest to decipher if you're not familiar with this stuff.

I ordered this book for a class on Causal Inference and Econometrics, and didn't have to dig it out until the middle of the semester. When I did, I noticed that the first chapter was missing, and that the second chapter is missing the first three pages. It is also out of order, which means that you can't read the integral first chapters of the book at all. Has anyone else had this problem?

The first thing I wish to say is this: If you plan on doing regression ysis in your research, stop what you are doing, and read this book first. I think this book represents THE current statement on how we should use regression. For Angrist and Pischke, regression is a technology for summarizing data. If regression is to be used for causal inference, then there is nothing in the specification of the model or the choice of estimator that can ultimately create the causal story persuasive. That is, you don't identify causal effects simply by including "control" variables in your regression. The identification comes from elsewhere---either a true or "quasi" experiment---and the regression is what you use to clean up the imperfections of the experiment and measure effects. Angrist and Pischke have done an enormous service to social science by writing a regression textbook that nonetheless emphasizes the primacy of design. This is a terrific corrective for the "101 flavors of regression" approach of textbooks to date.Even with this emphasis on design, Angrist and Pischke present us that are a lot of nuances to the method that regressions measure such effects---e.g., in the presence of result heterogeneity---and that's what this book explores in exquisite detail. It's a hugely necessary book and a very serious and rigorous treatment, despite it's apparently causal style. They create some claims that may strike some as outrageous---e.g., always using OLS, even for limited dependent variables---but the rigor of their presentation means that the onus is on those who disagree to think harder about why, exactly, they would prefer, say, a more parametric netheless, it isn't a "5 star" book. It often feels a bit rough-draft-like. The presentation of technical material skips necessary steps rather haphazardly. I wonder if this was due to poor editing? Hopefully there will be a second edition that cleans up these rough edges, in which case it would be the ideal textbook on regression ysis.

OK, let's be honest. There is nothing "harmless" about this book. Contrary to what the title suggests, it requires some serious background expertise in econometrics. So if you are looking for an introduction to econometrics, this is not your book. Instead, test Mastering Metrics by the same authors or Wooldridge's Introduction to Econometrics. If you are a complete beginner, Mastering Metrics might be the best eping this in mind, Mostly Harmless Econometrics is an perfect resource for those who have some background in econometrics and are interested in applying their theoretical knowledge to practical problems. I read this as part of my Ph.D. program in economics, and it was incredibly helpful. To be clear, you don't need a Ph.D. in economics to understand this, but having taken a class in econometrics or statistics is highly recommended.

I'm a PhD student in finance, and this book is phenomenal. Simple to read through, or to use as a reference on concepts (Greene is where you should go for the rigorous proofs, etc.), I actually have fun picking it up for class. I bought this for a seminar course, which will be my 3rd or 4th econometrics course, and I'm looking forward to reading this text for the class. If you're going into academia, this will be a lifelong companion, or so my Prof says; I assure you he's correct

Perfect companion book for those doing regression ysis. Understanding regression and its pros and cons are vital, and this book teaches that well. Very technical, but well-written. I use it for my PhD Econometrics class. It won't replace a course in regression or econometrics, but it's an perfect refresher or a amazing method to parallel the material if you're getting into the weeds of regression ysis.

I required to learn how to do happening history ysis to complete my dissertation. The book explains the subject in-depth and is simple to understand and follow. It does a really amazing job in explaining model choice and provides workable data to practice. A must have if you are learning happening history ysis in STATA!

this is probably the only book or source on Meta-ysis with Stata and for that I would give 3 stars however it leaves a lot to be desired.I am beautiful fluent with Stata and with Meta-anlaysis using other packages yet I am finding hard time following through this is small unconventional in that it is a collection of Stata Journal and technical Bulletin articles and doesn't give any instruction on the routines. It is though probably the only attempt that I know of that tried to address the wild wide west that is meta-ysis commands in Stata. There is significant room for improvement and there seems to be some degree of repetition of articles, they should just hold the e authors are the original authors of the Metan command and some of the articles are written by huge names in the MA e book could also use some organization in the sense that it should follow an instructional model with more explanation and provision of their example datasets for simulation.

**Matrix Differential Calculus with Applications in Statistics and Econometrics (Wiley Series in Probability and Statistics)**[] 2020-1-16 0:6

I am unusually lucky to obtain around the typesetting issues described by other reviewers: I was translating the book into Russian a few years ago based on the authors' LaTeX files, so I am not even sure I saw the Wiley book printed. I also was able to keep the author copy from the Russian publisher for free. Of course Wiley's price of $300 is ridiculous! The authors complained about it, too, seeing this as an objective obstacle for dissemination, but there is small they could do about the price.I have not appreciated the book that much until I hit the need for matrix calculus for my dissertation research. Knowing the book fairly closely, I was able to search the results I required in 15 minutes, and applying them to my issue provided a large leap in the generality of results, as well as shortened the derivations from about 15 pages of ugly element by element computations to about three pages. Two thumbs up!The book also includes a wealth of necessary mathematical results and makes the reader think rigorously about their notation (which is necessary for both matrix computations and for caclulus, thus making it at least twice as necessary in matrix calculus), so it can be targeted not only at statistical and econometric audiences, but can also serve as a useful supplement to a linear algebra course.

Poor book, badly written, disorganized, difficult to read chapters. It's supposed to be written for anyone, not only the legal students and professionals, but I'm finding more difficult to digest than any law textbooks. I read a lot, fiction and non-fiction, and this book is making me dizzy. The writer seems to know about environmental law but she doesn't know how to write about it. I want my school had picked something else.

First time I opened the book a bit of the binding popped out at the top of the page, but besides that first couple of pages, it's held together while I've read through at least 4 chapters. There's also a bit of writing in some of the pages that I wasn't created aware of before I created my purchase. Neither of these things bother me that much, but I could see how it might bother someone else. I was overall satisfied with ability to buy at a lower price than the school bookstore and the speed at which I received it.

The third addition of this book adds more on evapotranspiration, erosion, ditch designs and stream processes, Except for the remote sensing aspects of the book, which are very weak, it is not a poor reference book. The main issue I had with it are the powerful private views and opinions which have no put in a textbook. Students do not need to be preached ere are several other Hydrology books on the shop that give the same information, but in a more professional demeanor.

This is the easiest to read textbook I've ever used. This is a tough topic and this book makes it simple to understand. It would be amazing for undergrad courses in environmental law as well as for paralegal courses. It covers all the major environmental acts, and contains interesting features on major environmental happenings (like the Exxon Valdez s). It also contains profiles of specialists working in the field of environmental law. Finally, the images are really good, too.

It's a textbook for paralegals, but anyone in law or business (anyone with a job in today's world) would benefit greatly from Schroeder's work. Far from the typical global-warming alarmism, this book delivers honesty not only about threats to our natural environment, but those more insidious threats to our society posed by the troubles in our governmental and legal environments. This book is worth buying just for the photos! But the text is truly one-of-a-kind.

Bought this for 400-level wetlands course. Disappointed a lot of of the images are in black & white which makes seeing the info ry informative and worth hanging on to even after coursework is done if you plan to work in the field. Glad I have the digital ver since the printed ver has NO color photos.

Amazing book! Everything you could hope for in an environmental chemistry text. I truly have fun just reading it - a lot of history in this book on the development of the environmental science and historical environmental happenings and their impact on public health, resulting research and public policy. From water pollution, atmospheric geochemistry with pollution fate pathways this book is well-rounded for the introductory survey to this field. And, you can learn all the math of everything with practice problems!

I downloaded and rented the E-Book for a class I took over the course of 1 semester. It arrived just as any E book would, and I had no issues downloading it onto the Kindle application for IPad. It's a textbook, therefore I thought it was a beautiful dry read. however, I did have fun thinking about Des Jardins different points he makes about the ethics in the environment, where humans fall into the natural order, and how we can further expand our thoughts and private ethic to care about the globe around us. History and philosophy pave the method towards a private ethic (in my opinion) and I would say that I learned a amazing deal from this class with the aide of that book.

This book was needed for my college course, and I must say that this book was...interesting. This book is written in a method that if you're not fully into environmental ethics, it will be a hard read. There were points of the book where after reading a paragraph, I would have no idea what I just read because of the method its written. To anyone who must rent this book, amazing luck and you will obtain through this!

This book was for my class in College. I was excited about it, because I'm extremely environmentally conscious and thought that the topic matter would be an exciting debate. By the fourth chapter, I was dreading the reading. It turned out to be just a repetitive drone of a "survey of philosophy" with lots of quotes from philosophers. Hopefully, your teacher will be amazing enough to have boiled it down and focuses on the ideas behind the writing. I recommend renting this book, as you likely wouldn't read it twice.

**Matrix Differential Calculus with Applications in Statistics and Econometrics (Wiley Series in Probability and Statistics)**[] 2020-1-16 0:6

I was surprised to learn about the not good quality of typesetting in the paperback (second?) edition. I reviewed the book for JASA, when it first appeared, and, over the years, I've used it a lot of a lot of times. It is really a remarkable book, for allof us who need to deal with matrices in our daily research work.I was about to buy a second copy of the book, but the hardcover rice is ridiculous (more than $300!!), and I was turned away from buying the paperback edition because of the comments on the poor quality of is is too bad. A book of this stature deserves a better treatment by the publisher!

**Matrix Differential Calculus with Applications in Statistics and Econometrics (Wiley Series in Probability and Statistics)**[] 2020-1-16 0:6

For some reason, in spite of its enormous utility, matrix differential calculus is oddly absent from standard courses in signal processing and control. The amazing strength of this text is its focus on the development of sufficient and important conditions for constrained/unconstrained minima/maxima. There are amazing examples regarding maximum likelihood estimation. There are also some useful results regarding the Kronecker product and commutator matrices. The chapter at the end covers specific subjects in econometrics. The paperback edition suffers from completely hideous typesetting that is exacerbated by some of the notation. In spite of the fact that the paperback is not cheap, the pages look like they were photocopied. Maybe I just got a poor copy. I don't know if the hardback edition has the same problem.

This book is seriously one of the most clear and concise textbooks I have read for the latest ten years. I want I would have discovered it sooner. It is so beautifully written it makes my eyes hurt. I am almost wishing it would cost more so I could give them more money.

Matrix differential Calculus is probably not something you might encounter everyday, but if you do then this is the book that will tutorial you through everything relevant thing that you need to know about it. The book is educational in the sense that it walks you through matrix theory and linear algebra and then advances into calculus and more advanced topics. However, what I also search very beautiful about this book is that it can serve as a reference. Whenever you are held up by an issue, you just browse through the book and search some theorem or formula that quickly resolves the situation for you. So I would recommend that you a copy on your shelf to go to repeatedly.

I have read the poor reviews regarding the typesetting of this book and I thought they were exaggerating. Nevertheless, I have borrowed this book (old edition/hardcover) from the University library and I thought that buying it was worthwile.When I ordered the book I found out that the book quality was even worse than expected. The typesetting is worse than a photocopied book; I even thought that this was not an authentic copy but a cheap one from a Banana country. Nevertheless, when you begin to read the book pages are coming out. The hardcover edition price -$300$- is ridiculous. I am a postoctoral fellow in engineering and I cannot afford more than $100 for a book. The $80 dollar price is not justified for that poor typesetting. This is a very helpful book for a graduate engineering student but I doubt that I will recommend it for buying. I will have to think seriously about buying another book from Wiley piblishers.

This book comprehensively covered the theory and implementation if matrix differentiation. However, the theory may be a small much for those approaching from a more practical e chapters on psychometrics and instrumental models weren’t stellar in my opinion.

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Applied Statistics Using Stata: A Guide for the Social Sciences[] 2020-5-2 18:12Clear and informative

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Multilevel and Longitudinal Modeling Using Stata, Volumes I and II[] 2020-12-3 18:59Amazing content. The index in this book is weak weak weak.

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Multilevel and Longitudinal Modeling Using Stata, Volumes I and II[] 2020-12-3 18:59Usually, to master a modeling technique, the student has to consult more than one source. However, if you only had to use one book to do multilevel ysis then this is the book you should go for. The authors begin from the easy model which assumed independence between the various observations and slowly build more complicated models while explaining both the strengths and weaknesses of the added complexity. This book is excellent or Stata users because along with the theory the authors also explain the Stata output. I search it frustrating that there are several commands that you can use for this type of modeling, each with its advantages, but the authors do a very amazing job of explaining the differences so the user doesn't obtain mixed up. I have used this book to study multilevel models for my PhD thesis, but it was not the only book that I used. If I were to be very picky and target one item which was better presented in another book, it would definitely be the the building up of models, taking unique care about the time variable, in longitudinal datasets. I used Applied Longitudinal Data ysis by Singer and Willett for this particular issue. Unlike the show book, the book by Singer and Willett is mainly concerned with longitudinal datasets and hence they devote a lot of time to explaining how time should be treated. However, the book by Rabe-Hesketh and Skrondal is much more comprehensive and has the added value of including detailed commands and output from Stata. This sort of book makes me glad that I decided to learn Stata and not another statistical package.

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