4/30/2012

Explaining Psychological Statistics Review

Explaining Psychological Statistics
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For a while, I was looking for a good book on statistics, and finally, I found it! This book is excellent for those who are going to start learning statistics (every thing is explained very well from very beginning!) as well as for those (like me) who look for more advanced books. It is almost perfect! It has precise and clear explanations, simple brief examples, thoughtfully chosen questions and tasks at the end of each chapter, good overall organization. Every word (well, sentence) contributes to understanding of concepts, no unnecessary information, no waste of time. Every new concept is built on the previous ones, no gaps in explanation, no unanswered questions. It feels as if the author follows a reader's mind, if some questions arise they get answered in the next paragraphs. Pure pleasure! Ultimate book on statistics! Highly recommend.

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4/29/2012

Visualization of Categorical Data Review

Visualization of Categorical Data
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Having read a lot of conference proceedings in my time I would say this is better than most. Don't read this if you want a coherent view of data visualisation. It's a mixture of cutting edge stuff, work in progress, reports on what has worked in practice, plus a couple that were probably written as their employer won't send them to a conference unless they present *something*. As I said, a typical conference mixture. Usually I'm delighted if more than 5% of the papers are of interest. The yield is about 20%. I am interested in what works in practice for the statistical illiterate user in a survey environment. So I look for data visualisation in terms of putting statistical understanding in the graph without the user knowing. So for me some of the papers are useful, but if you're interested in some other aspect, well, you'll be interested in other papers. I must admit some of the papers had me thinking they're stretching the title of this. Michael Friendly's paper was interesting as usual, though not much not already out there (see recent JASA?). The Billiet et al paper I found particularly useful. I have found biplots are a useful, if rather underutilised method. Ditto for the Gabriel paper. Blasius paper is raising interesting ideas, and I feel it should feed into cognitive testing. A bit of a fan of CART, so the Lausen paper was interesting, though I always assumed CART was an EDA technique, rather than an end in itself. the Whittaker paper gave me some food for thought. The Windmoller, Voges & Francis papers were interesting to me, even given their rather subject-matter foci. I find how someone analyses data is sometimes useful, even if I'm not working in that field, as was the case here. Summary: Can't say I'd personally buy it, but would recommend any decent technical library to buy.

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A unique and timely monograph, Visualization of Categorical Data contains a useful balance of theoretical and practical material on this important new area. Top researchers in the field present the books four main topics: visualization, correspondence analysis, biplots and multidimensional scaling, and contingency table models.This volume discusses how surveys, which are employed in many different research areas, generate categorical data. It will be of great interest to anyone involved in collecting or analyzing categorical data. * Correspondence Analysis* Homogeneity Analysis* Loglinear and Association Models* Latent Class Analysis* Multidimensional Scaling* Cluster Analysis* Ideal Point Discriminant Analysis* CHAID* Formal Concept Analysis* Graphical Models

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4/28/2012

Principles and Practice of Structural Equation Modeling, Second Edition (Methodology In The Social Sciences) Review

Principles and Practice of Structural Equation Modeling, Second Edition (Methodology In The Social Sciences)
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Kline's book provides a very readable introduction to and explanation of structural equation modeling. The book does not include statistical proofs, so it would not serve well as an advanced text. But if you are looking for a book that explains what SEM is and how it fits within the larger framework of inferential statistics, I recommend it.

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The bestselling text that has been so popular with graduate students and researchers for providing an accessible guide to the application, interpretation, and pitfalls of structural equation modeling (SEM) has now been carefully revised to be even more useful.New to this edition are: * The first SEM text web page, offering free access to data and program syntax files for many of the research examples in the book, electronic overheads that readers can download and print, and links to other useful sites. * Separate chapters that review fundamental statistical concepts: one on correlation and regression (providing a foundation for less advanced readers), and another on data preparation and screening. * More coverage of the relation between measurement models and structural models in Chapter 8, which directly compares both types of models. * New, separate chapters on nonrecursive models of multiple-sample SEM in Part III, including extensive explanations of latent growth models in Chapter 10 and multilevel SEM in Chapter 13.

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4/27/2012

Presenting Your Findings: A Practical Guide for Creating Tables Review

Presenting Your Findings: A Practical Guide for Creating Tables
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This book has been needed for twenty years. Students and professional researchers who write dissertations and manuscripts using APA style have desperately needed this very helpful resource. The book illustrates standard presentation tables for more than twenty types of standard statistical tests. The concept of "Play It Safe" tables will save researchers hundreds of hours of time. The table illustrations are clear and precise depending on the focus of the data to be presented. The few words that are written prior to presenting a table are helpful in clarifying the data contained in the tables. One small problem is noted. It would have been helpful to include how APA style recommends reporting statistical data in paragraph form in this book also. Despite this omission, I still give this book 5 stars.

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Helpful reference for students and researchers wishing to publish their research findings. Answers specific questions regarding the presentation of data using a variety of statistical analyses. Provides flexible tabular formats, examples, notes, and formatting tips. Softcover.

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4/26/2012

Foundations of Behavioral Statistics: An Insight-Based Approach Review

Foundations of Behavioral Statistics: An Insight-Based Approach
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This is a great book for all ages including elementary school kids. My fourth grader enjoyed reading the chapter on central tendendy -- mean, median and mode -- and she doubly enjoyed reading about these things through an easy to read graduate level textbook while learning them at school at the same time. She asked to keep that book for her. I wish I had that book when I was a fourth grader as well!
It includes many examples from real life studies -- including an example from the famous LibQUAL+(R) protocol that libraries all over the world use to evaluate their services. You get extra bonus marks if you can explain the LibQUAL+(R) example and you are a librarian!
Martha Kyrillidou, Director of Statistics and Service Quality Programs, Association of Research Libraries

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With humor, extraordinary clarity, and carefully paced explanations and examples, Bruce Thompson shows readers how to use the latest techniques for interpreting research outcomes as well as how to make statistical decisions that result in better research. Utilizing the general linear model to demonstrate how different statistical methods are related to each other, Thompson integrates a broad array of methods involving only a single dependent variable, ranging from classical and robust location descriptive statistics, through effect sizes, and on through ANOVA, multiple regression, loglinear analysis and logistic regression. Special features include SPSS and Excel demonstrations that offer opportunities, in the book’s datasets and on Thompson’s website, for further exploration of statistical dynamics.

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4/25/2012

Blackwell Handbook of Research Methods in Industrial and Organizational Psychology (Blackwell Handbooks of Research Methods in Psychology) Review

Blackwell Handbook of Research Methods in Industrial and Organizational Psychology (Blackwell Handbooks of Research Methods in Psychology)
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Steven's daughter is the coolest kid in the world... Everyone should buy this book because it is dedicated to Sasha and Sasha Rocks!!!!!!!

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Handbook of Research Methods in Industrial and Organizational Psychology is a comprehensive and contemporary treatment of research philosophies, approaches, tools, and techniques indigenous to industrial and organizational psychology. In this volume, leading methodological and measurement scholars discuss topics spanning the entire organizational research process. Topics include, but are not limited to, research ethics, reliability and validity, research design, qualitative research paradigms, power analysis, computational modeling, confirmatory factor analysis, internet data collection, longitudinal modeling, modeling complex data structures, multilevel research, cross-cultural organizational research, and modeling nonlinear relationships. Chapters are written so that both the novice and the experienced researcher will gain new and useful practical and theoretical insights into how to systematically and pragmatically study work-related phenomena. This handbook will serve as an excellent modern complement to other more content-based handbooks of industrial/organizational psychology, organizational behavior, and human resources management.

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4/24/2012

Lossless Compression Handbook (Communications, Networking and Multimedia) Review

Lossless Compression Handbook (Communications, Networking and Multimedia)
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The book is probably the best technical reference on lossless compression ever published. All aspects of the book deserve kudos. It contains up to the date and to the point professional coverage of a wide field presented with an exceptional clarity. The balance between practical and theoretical aspects is excellent.
The book is mostly self-contained thanks to the intro part on the basics of information and complexity theory. The intro, despite its modest size, is superior to many dedicated textbooks. The other three main parts discuss compression techniques, applications and standards. The chapters are written by different authors and, as can be expected, are not all equal in terms of depth or practical applicability. However, all of them provide a list of well selected references, which compensate for some of the shorter chapters. The editors and the authors did a great job on delivering the text which is quite uniform in style, highly informative and yet very readable and digestible throughout the entire book.
Most methods are explained with enough details to start your own research or implementation. Whenever possible the authors compare different methods with tables and graphs. Thus, before a reader jumps into coding, (s)he can make an intelligent choice. (This, btw, comes from my personal experience. The next day after arrival the book helped me to find a better replacement for an inhouse method of encoding.)
Practitioners will also appreciate discussion of patent issues and possible workarounds, when applicable.
Bottom line - this is one of the most useful technical books I bought. A must have for anyone working with data compression.

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4/23/2012

Probability and Statistics for Engineering and the Sciences (with Student Suite Online) Review

Probability and Statistics for Engineering and the Sciences (with Student Suite Online)
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Given any particular university level textbook, there's always a compromise between the author's need to write a professional text and concurrently make it easy to understand. This textbook is no exception, and it leans toward the professional aspect. It is therefore good reference or supplementary material for those who already have some background in statistics, but it is very difficult to learn from the text alone.
As for the book itself, it has strengths and weaknesses. On the good side, it has excellent examples that use real world data, albeit largely from esoteric sources. You can see right off that knowing the material will be very useful in real-world applications, which isn't something you get from many other textbooks.
If you happen to be interested in statistical theory, this book has everything you'd want to know and more. Some of the details get pretty gory, but if you like that sort of thing, it's all here. At the same time, the text is organized so you can easily skip those parts if it's not your ballgame.
The layout and organization, in general, are well thought out and implemented. Important formulas are boxed for easy identification, and key terms are well referenced. The book size and weight is also very reasonable for a textbook. This is attained by very concise, mathematical language. Also, a useful CD is included with the text, containing all the data used in the exercises (various program formats) so you don't have to type it all in manually. All-important tables are located in the back of the book, where you can always find them. Additionally, the appendix section has answers to the odd-numbered exercises. It's not that much of a problem that you only have half the solutions, because concurrent problems are usually similar.
Downsides to the text include the language, which is highly technical, relying heavily on symbols, terminology, and acronyms. Of course, statistics in general is like this, but this book really forces you to learn this rather distasteful aspect of the field. Anyway, it could certainly be more user-friendly, although as such it might be less concise. For those who are well accustomed to such things (e.g. statisticians, mathematicians, military people) the material might be an easy thing to pick up. For others, it can be frustrating when you have to flip back a few hundred pages to remind yourself what a particular Greek alphabet was supposed to represent. Personally, I feel a table of all the symbols with a brief description of each would have been a very welcome addition to the appendix.
Though the exercises are generally well done and challenging, I do have some issues with them. From time to time, one would refer to a problem or data set from way back in the textbook- with no executive summary. It would have been nice to be able to see what was being asked without flipping back hundreds of pages. Additionally, the answers provided in the appendix are often nearly useless, since a terse numerical answer says little about how you might arrive at it. For this purpose there is a solutions manual available, but you might be disinclined to pay for it.
The most prominent difficulty with the text- and I know it's not exclusively mine- is the simple fact that it is a professional work. If you have no knowledge of statistics beforehand, it can be an extremely difficult read. For a while I tried to browse the text before lectures, but I found that it wasn't worth the effort. It took so long to plow through to the 'moral of the story' that I ended up just using the book for review. Fortunately, I was lucky enough to have an excellent statistics professor (the author himself) and so was able to pick up the concepts by simply going to class. If, in the admittedly improbable event that you're new to statistics and are looking for an extra book to make up for a poor instructor, you might want to look at a different one. If you already know something about statistics and want a useful reference, then this is your resource.

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This comprehensive introduction to probability and statistics will give you the solid grounding you need no matter what your engineering specialty. Through the use of lively and realistic examples, the author helps you go beyond simply learning about statistics to actually putting the statistical methods to use. Rather than focus on rigorous mathematical development and potentially overwhelming derivations, the book emphasizes concepts, models, methodology, and applications that facilitate your understanding.

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4/22/2012

Neural Network Data Analysis Using Simulnet Review

Neural Network Data Analysis Using Simulnet
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Mr. Rzempoluck covers neural network theory quite well, but be aware that the software is very poor! There seems to be little correlation between the book and software, leading to endless frustration. In my humble opinion, you would be better off purchasing one of the other Neural Network tutors out there. They cover the same ground and don't seem to have the obtuse approach that this text sometimes takes.

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This book and sofwtare package provide a complement to the traditional data analysis tools already widely available. It presents an introduction to the analysis of data using neural networks. Neural network functions discussed include multilayer feed-forward networks using error back propagation, genetic algorithm-neural network hybrids, generalized regression neural networks, learning quantizer networks, and self-organizing feature maps. In an easy-to-use, Windows-based environment it offers a wide range of data analytic tools which are not usually found together: these include genetic algorithms, probabilistic networks, as well as a number of related techniques that support these - notably, fractal dimension analysis, coherence analysis, and mutual information analysis. The text presents a number of worked examples and case studies using Simulnet, the software package which comes with the book. Readers are assumed to have a basic understanding of computers and elementary mathematics. With this background, a reader will find themselves quickly conducting sophisticated hands-on analyses of data sets.

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4/21/2012

Cardiogenic Shock Review

Cardiogenic Shock
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This book covers all the problems that wake cardiology fellows up at night in a cold sweat. Everything from electrical storm to IABP insertion and management.
Not only reviews the basics and epidemiology of cardiogenic shock, but also the difficult issues which face many critical care physicians. A must read and must buy for any nurse or physician involved in the care of cardiac patients.

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Rush-Presbyterian-St. Luke's Medical Center, Chicago, IL. Provides a detailed overview of the current state of knowledge about cardiogenic shock. For clinicians and researchers. DNLM: Shock, Cardiogenic-diagnosis.

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4/20/2012

The Missing Keys to Thriving in Any Real Estate Market Review

The Missing Keys to Thriving in Any Real Estate Market
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Reviewed by Randy A Lakin for RebeccasReads (11/09)
I found Eddie Godshalk's new book, "The Missing Keys to Thriving in Any Real Estate Market," very enlightening. There are so many factors to consider when you look at the real estate market today. While I may not be a real estate investor or professional, I found the information laid out by the author to be very educational. The author covers several areas that lead the Real Estate market to where it is today. The author, Eddie Godshalk, talks about what is known as, "Predatory Lending". So many lenders targeted the lower income, high credit risk markets. The author tells how they pushed those buyers into Adjustable Rate Mortgages or ARM's as they are called. In "The Missing Keys to Thriving in Any Real Estate Market", the author explains about Builders acting as Lenders and how their use of creative financing freed them of the liability that so many other lenders had to contend with.
The author explains about a new breed of real estate investor that emerged known as the, "House Flipper". The author explains how they would purchase a house, and then invest a few thousand dollars in renovations. Just to sell it before the first payment was due, thus making several thousands of dollars in profit. The author also points out that along with the "house flipping", came many do-it-yourselfers and several television shows showing you how to do it yourself.
On key point that the author makes is the "Magic Tool known as the Home Value Predictor". This software enables the investor to find the critical missing information quickly and easily, allowing for proper, well-informed real estate decisions. All this information is in Eddie Godshalk's book, and it is laid out in an easy-to-understand approach. The author gives you a lot of information; however, he does so in an easy-to-read fashion. I think you will find this book a good investment, no matter your real estate background. It is well worth the reasonable investment verses the knowledge you will gain from it.

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"The Missing Keys to Thriving in Any Real Estate Market - How to Create Wealth in Any Community Using Street Analysis Technology" It is risk reduction blueprint for Investors and Real Estate professionals who want to be experts in there local market and make more sales. Readers will learn how to and where to get current accurate info and not be mislead by the media and create wealth using break-through mapping technology.

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4/19/2012

A Virtuous Circle: Political Communications in Postindustrial Societies (Communication, Society and Politics) Review

A Virtuous Circle: Political Communications in Postindustrial Societies (Communication, Society and Politics)
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Michael Schudson - Columbia Journalism Review Sept 2000 "Correlation is not causation." That is as basic a watchword for social science as "watch the ball" is for athletics. And it is the guiding principle that informs this important rethinking of the influence of news on our political culture.
There's more meat here than even author Pippa Norris has herself digested; the book is half social science analysis and half a statistical almanac. But this is to quibble. A Virtuous Circle is praiseworthy both for its sumptuous comparative statistics on the news media across European and North American democracies, and for its unflappable sanity and even ruddy hopefulness about the state of the media (but not necessarily the state of the world) today.
For Norris, media critics have failed to make their case that contemporary news practices harm the body politic. The evidence of "media malaise," that media and political communication today reduce civic activism, diminish trust in government, and retard knowledge of and interest in public affairs, has little empirical support. In fact, people who attend to news know more about politics than those who don't. They are as trusting of political institutions as those less attentive to news.
This is not exactly three cheers for the press, but it directly counters the views of many others -- including Norris's own distinguished colleague at Harvard's Shorenstein Center, Thomas Patterson (it makes you wonder what their faculty meetings are like).
In l993, Patterson published a widely noted book, Out of Order, that claimed that the U.S. news media had grown more negative and more cynical in political coverage over the past two or three decades, that this had matched a growing popular distrust of politicians and government and a general disengagement from civic life, and that -- although Patterson also knows that "correlation is not causation" -- cynicism in the news "has contributed to" cynicism in the electorate. Other scholars, journalists, and media reformers have endorsed a "the news-media-make-us-less-civic" hypothesis. A European version of this argument focuses more on the increasingly media-oriented electoral campaigns than on the news as such. In the European variant, American-style political packaging, media consultants, and emphasis on image over substance have produced a European "crisis of civic communication."
Well, Norris asks, in her "I call 'em as I see 'em" tone, what do the data tell us? As a comparative political scientist, a British transplant to the United States and a student of British as well as U.S. media and politics, she also suspects the American situation might look different when compared to other nations. If there is "media malaise," is it an American disease or a world epidemic?
Here's what she finds. In Europe since l970, the percentage of citizens of democracies who read a newspaper every day has grown by 67 percent. The percentage of people who watch television news daily has increased almost 50 percent. Even after taking education into account, European citizens who attend to news know more about politics as well as everyday social and health matters than those who do not. People attentive to news are no more, but no less, trusting and confident in government than the inattentive. People attentive to news are more likely to participate in politics through voting and other forms of participation. Looking specifically at news coverage of the European Union, Norris found a "Euroskeptic tone" in the newspapers and an even more negative tone in European TV news and she found this associated with public skepticism toward the euro and other features of the EU. But she resists drawing the conclusion that this is a case of the press influencing the public. Instead, she argues, the press takes its cues from party elites, interest groups, and the political culture at large; journalists are "players in a broader political culture" rather than outsiders independent of it.
In America, the media domain is very different, with lack of newspaper competition in most markets, the absence of the kind of strong tabloid readership that many European countries maintain, falling rather than rising newspaper sales, and the absence of a strong public-service broadcast sector. Does a "media malaise" hypothesis work better here? No. As in Europe, people who attend to the news are significantly more likely to participate in political campaigns by voting, contributing money, or discussing politics. It may be that watching hour after hour of entertainment television is a factor in disengaging Americans from political and civic life, but watching TV news is not. Norris does not find any relationship between increasing negativism in the news since the l980s and popular trust in governing institutions, which has risen, fallen, and risen again in this same period. She finds a decline in political interest, political trust, and voter turnout in the 1960s-early 1970s, but not a steady decline from the l960s to the present. Not only is correlation not causation -- we don't even have a good correlation.
The evidence for media-driven malaise just ain't there. The best evidence, in fact, goes in the other direction: that active, politically engaged people attend to the news more than others and that attending to the news reinforces them in their political involvement. This is the "virtuous" rather than "vicious" circle of her title. And in most respects she is utterly convincing.
This is a significant book. It is, to be sure, an academic's book. Although Norris writes clear and straightforward prose, she also gets caught up in the intricacies of academic argument and a range of data so vast that the general reader will have a tough time of it. But her conclusion is challenging: "A citizenry that is better informed and more highly educated, with higher cognitive skills and more sources of information, may well become increasingly critical of governing institutions, with declining affective loyalties towards traditional representative bodies such as parties and parliaments. But increasing criticism from citizens does not necessarily reduce civic engagement; indeed, it can have the contrary effect." In other words, the tenor of the times is more critical than it used to be, with uncertain consequences. Norris wants us to consider the possibility that critical citizens, committed to democratic values but unhappy with the performance of governmental institutions, are not cynical but wary. And vigilance can be a democratic virtue.
This is not to suggest, Norris cautions, that all's well in contemporary democracies. But blaming the news media for what ails us in political corruption, undernourished social services, and violent conflicts in some countries is to find a scapegoat, not a powerful source of our ills.
Michael Schudson is professor of communications and sociology at the University of California. His latest book is A Good Citizen: A History of American Civic Life.
===============================================================
UNCONVENTIONAL WISDOM
By Richard Morin Sunday, September 17, 2000; Page B05
The Myth of Media Malaise
For decades, it's been hugely fashionable in academe to finger the cynical and superficial news media as the cause of rising levels of civic disengagement.
Well, democracy may or may not be in eclipse, and people certainly don't trust politicians or vote nearly as often as they did a few decades ago. But don't blame the media, argues political scientist Pippa Norris in her new book "A Virtuous Circle: Political Communications in Postindustrial Societies."
Norris, a professor at Harvard, examined five decades of polling data from several major surveys conducted in the United States, as well as surveys conducted in Europe. Wherever she looked, Norris found that people who read newspapers or watch TV network news more frequently are generally more trusting, less cynical and more knowledgeable about politics and government--even after she controlled for their education, income, gender, age and other variables that shape political attitudes.
Rather than driving down political involvement and ratcheting up mistrust, Norris says that attention to the news "acts as a virtuous circle: The most politically knowledgeable, trusting and participatory are most likely to tune to public affairs coverage. And those most attentive to coverage of public affairs become more engaged in civic life."
Then who's responsible for creating the tattered image of the malaise-making news media? Blame it, at least in part, on the media themselves, which Norris says have become increasingly preoccupied with "self-flagellation."
The resulting false picture, she cautions, does real harm--but not to civic life. Rather, it erodes public confidence in the news media. Plus, it's so predictable. "American journalism seems increasingly transfixed by American journalism, looking at itself obs

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Is the process of political communications by the news media and by parties responsible for civic malaise? A Virtuous Circle sets out to challenge the conventional wisdom that it is. Based on a comparative examination of the role of the news media and parties in postindustrial societies, this study argues that rather than mistakenly "blaming the messenger" we need to understand and confront more deep-rooted flaws in the systems of representative democracy.

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4/18/2012

Statistical Analysis of Gene Expression Microarray Data Review

Statistical Analysis of Gene Expression Microarray Data
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Microarray studies are becoming the preferred research tools in many areas, including cancer research, development studies, and studies in organisms' responses to their environments. Because of differences between organisms or between experiments, microarray data is always statistical in nature. The problem is that the data aren't well suited to traditional statistics. Instead of studying a few characteristics in large numbers of individuals, microarray studies typically yield thousands of data values for a few dozen samples.
That mismatch, between current statistical practice and microarray analysis requirements, seem to be driving many innovations in statistical analysis. This book is a brief survey of four of those areas of analysis: model-based analysis, experimental design, classification, and clustering.
The first section, on model-based analysis, is brief. Mostly, it seems to establish the language used in later sections. The next, on experimental design, deals with ways for getting the most information out of the fewest samples. The costs of arrays and processing are dropping, but still high. More analysis on less data makes good economic sense. The DNA samples analyzed also have costs - some can only be prepared in minute amounts, others must be extracted surgically from human patients. Either way, it's important to maximize the knowledge harvested from limited amounts of biologcal material.
The next section, on discrimination, is a bit longer. It briefly summarizes a wide variety of techniques for deciding which category best represents any one sample. This section gives a good review of analytic approaches: Fisher classifiers and their descendants, principal components, support vectors, and decision trees. Within trees, the authors note that the number of missing values in typical microarray data may interfere with standard analysis, and that surrogate variables may be needed in many cases. AI and data mining techniques aren't broadly represented, but this chapter is still very informative.
The final section, on clustering, was shorter. It was reasonably informative, and I gleaned a few new facts from it. Mostly, though, it seemed to present techniques that are already well known.
This book is a survey, so it emphasizes breadth over depth. Many algorithms described only briefly, and some are just mentioned by name. The developer will need to chase references to find an implementable level of detail. Still, the book has value as an index to references and as a comparison of techniques.
//wiredweird

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Although less than a decade old, the field of microarray data analysisisnow thrivingand growing at a remarkable pace. Biologists, geneticists, and computer scientists as well as statisticians all need an accessible, systematic treatment of the techniques used for analyzing the vast amounts of data generated by large-scale gene expression studies. And there is arguably no group better qualified to do so than the authors of this book.Statistical Analysis of Gene Expression Microarray Data promises to become the definitive basic reference in the field. Under the editorship of Terry Speed, some of the world's most pre-eminent authorities have joined forces to present the tools, features, and problems associated with the analysis of genetic microarray data. These include::"Model-based analysis of oligonucleotide arrays, including expression index computation, outlier detection, and standard error applications"Design and analysis of comparative experiments involving microarrays, with focus on \ two-color cDNA or long oligonucleotide arrays on glass slides "Classification issues, including the statistical foundations of classification and an overview of different classifiers"Clustering, partitioning, and hierarchical methods of analysis, including techniques related to principal components and singular value decompositionAlthough the technologies used in large-scale, high throughput assays will continue to evolve, statistical analysis will remain a cornerstone of their success and future development. Statistical Analysis of Gene Expression Microarray Data will help you meet the challenges of large, complex datasets and contribute to new methodological and computational advances.

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4/17/2012

Conducting Meta-Analysis Using SAS (Multivariate Applications Series) Review

Conducting Meta-Analysis Using SAS (Multivariate Applications Series)
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The focus of this book on Glassian (d) and Hunter and Schmidt (r) approaches to meta-analysis really limits the usefulness of the book. Examples are limited to social sciences literature in which these approaches have been used. Do not buy if you want techniques publishable in other literatures.

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Conducting Meta-Analysis Using SAS reviews the meta-analysis statistical procedure and shows the reader how to conduct one using SAS. It presents and illustrates the use of the PROC MEANS procedure in SAS to perform the data computations called for by the two most commonly used meta-analytic procedures, the Hunter & Schmidt and Glassian approaches.This book serves as both an operational guide and user's manual by describing and explaining the meta-analysis procedures and then presenting the appropriate SAS program code for computing the pertinent statistics. The practical, step-by-step instructions quickly prepare the reader to conduct a meta-analysis. Sample programs available on the Web further aid the reader in understanding the material.Intended for researchers, students, instructors, and practitioners interested in conducting a meta-analysis, the presentation of both formulas and their associated SAS program code keeps the reader and user in touch with technical aspects of the meta-analysis process. The book is also appropriate for advanced courses in meta-analysis psychology, education, management, and other applied social and health sciences departments.

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4/16/2012

Introduction to Statistics Through Resampling Methods and Microsoft Office Excel Review

Introduction to Statistics Through Resampling Methods and Microsoft Office Excel
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This book is fine if you want to learn about resampling, but if you are interested in learning how to program the algorithms in Excel this is not the book for you. The author is using the book to promote certain Excel ad-ins and if that is what you want then that's great. If like me you wanted to do the programming yourself, then this book is not as useful as the title suggests and is a bit misleading.
The title of the book would have been more accurate if it said "Introduction to Statistics Through Resampling Methods and using Add-ins for Microsoft Excel".

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Learn statistical methods quickly and easily with the discovery methodWith its emphasis on the discovery method, this publication encourages readers to discover solutions on their own rather than simply copy answers or apply a formula by rote. Readers quickly master and learn to apply statistical methods, such as bootstrap, decision trees, t-test, and permutations to better characterize, report, test, and classify their research findings. In addition to traditional methods, specialized methods are covered, allowing readers to select and apply the most effective method for their research, including:* Tests and estimation procedures for one, two, and multiple samples* Model building* Multivariate analysis* Complex experimental designThroughout the text, Microsoft Office Excel(r) is used to illustrate new concepts and assist readers in completing exercises. An Excel Primer is included as an Appendix for readers who need to learn or brush up on their Excel skills.Written in an informal, highly accessible style, this text is an excellent guide to descriptive statistics, estimation, testing hypotheses, and model building. All the pedagogical tools needed to facilitate quick learning are provided:* More than 100 exercises scattered throughout the text stimulate readers' thinking and actively engage them in applying their newfound skills* Companion FTP site provides access to all data sets discussed in the text* An Instructor's Manual is available upon request from the publisher* Dozens of thought-provoking questions in the final chapter assist readers in applying statistics to solve real-life problems* Helpful appendices include an index to Excel and Excel add-in functionsThis text serves as an excellent introduction to statistics for students in all disciplines. The accessible style and focus on real-life problem solving are perfectly suited to both students and practitioners.

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4/15/2012

Modern Methods for Business Research (Quantitative Methodology Series) Review

Modern Methods for Business Research (Quantitative Methodology Series)
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I've used a couple of chapters out of this book fairly extensively. They are easy to follow, interesting, and provide strong applied examples of techniques. Really useful for researchers interested in SEM techniques!

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This volume introduces the latest popular methods for conducting business research. The goal of each chapter author--a leading authority in a particular subject area--is to provide an understanding of each method with a minimum of mathematical derivations. The chapters are organized within three general interrelated topics--Measurement, Decision Analysis, and Modeling. The chapters on measurement discuss generalizability theory, latent trait and latent class models, and multi-faceted Rasch modeling. The chapters on decision analysis feature applied location theory models, data envelopment analysis, and heuristic search procedures. The chapters on modeling examine exploratory and confirmatory factor analysis, dynamic factor analysis, partial least squares and structural equation modeling, multilevel data analysis, modeling of longitudinal data by latent growth curve methods and structures, and configural models of longitudinal categorical data.

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4/14/2012

Statistics for Microarrays: Design, Analysis and Inference Review

Statistics  for Microarrays: Design, Analysis and Inference
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This is the best introduction I know for anyone trying to learn the bioinformatics of microarrays. It starts with a brief description of the DNA microarrays, their chemistry, and the sources of uncertainty in their measurements, just enough for a non-biologist to get the general ideas. It skips the steps of scanning and spot recognition, mostly, and jumps right into analysis of the array of spot readings.

That is where the text comes into its own. One happy surprise is the book's emphasis on quality control and error management. Quality issues are addressed first by themselves, then as they affect the design and analysis of an experiment's biological meaning. This covers a wide variety of issues, including dye swaps, array background correction, and inference in the presence of low-quality data. There are soft spots in the discussion, especially in handling of missing data. That fits the general tone of the book, though, by stressing understanding over rigor.

This book comes with a macro package for the R environment, an open-source system somewhat like Matlab or Mathematica. That is both the strength and the weakness of this book. The strength of course, is the working code. It lets you see a real implementation of the algorithms that the authors describe. The weakness is that the implementations don't explain how the algorithms were developed, why they work, or how to recognize when they've been pushed past their breaking points. If you need more than rote recitation of the authors' implementation, you may find this frustrating. Also, the book uses five data sets for concrete discussion, but the software kit seems to include only one.

Microarray data sets (a few individual with thousands of measurements each) are very different from standard statistical data sets (lots of individuals with few measurements each). Despite the dramatic improvements of the last few years, the processing of the arrays themselves still varis widely under even the tightest control. Microarrays really do need different kinds of analysis and experimental design. This is a very readable explanation of why and how those procedures are used. I just wish the procedures themselves were presented in a little more depth.
//wiredweird

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Interest in microarrays has increased considerably in the last ten years. This increase in the use of microarray technology has led to the need for good standards of microarray experimental notation, data representation, and the introduction of standard experimental controls, as well as standard data normalization and analysis techniques. Statistics for Microarrays: Design, Analysis and Inference is the first book that presents a coherent and systematic overview of statistical methods in all stages in the process of analysing microarray data – from getting good data to obtaining meaningful results.
Provides an overview of statistics for microarrays, including experimental design, data preparation, image analysis, normalization, quality control, and statistical inference.
Features many examples throughout using real data from microarray experiments.
Computational techniques are integrated into the text.
Takes a very practical approach, suitable for statistically-minded biologists.
Supported by a Website featuring colour images, software, and data sets.

Primarily aimed at statistically-minded biologists, bioinformaticians, biostatisticians, and computer scientists working with microarray data, the book is also suitable for postgraduate students of bioinformatics.

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