Missing Middle Housing


Book Description

Today, there is a tremendous mismatch between the available housing stock in the US and the housing options that people want and need. The post-WWII, auto-centric, single-family-development model no longer meets the needs of residents. Urban areas in the US are experiencing dramatically shifting household and cultural demographics and a growing demand for walkable urban living. Missing Middle Housing, a term coined by Daniel Parolek, describes the walkable, desirable, yet attainable housing that many people across the country are struggling to find. Missing Middle Housing types—such as duplexes, fourplexes, and bungalow courts—can provide options along a spectrum of affordability. In Missing Middle Housing, Parolek, an architect and urban designer, illustrates the power of these housing types to meet today’s diverse housing needs. With the benefit of beautiful full-color graphics, Parolek goes into depth about the benefits and qualities of Missing Middle Housing. The book demonstrates why more developers should be building Missing Middle Housing and defines the barriers cities need to remove to enable it to be built. Case studies of built projects show what is possible, from the Prairie Queen Neighborhood in Omaha, Nebraska to the Sonoma Wildfire Cottages, in California. A chapter from urban scholar Arthur C. Nelson uses data analysis to highlight the urgency to deliver Missing Middle Housing. Parolek proves that density is too blunt of an instrument to effectively regulate for twenty-first-century housing needs. Complete industries and systems will have to be rethought to help deliver the broad range of Missing Middle Housing needed to meet the demand, as this book shows. Whether you are a planner, architect, builder, or city leader, Missing Middle Housing will help you think differently about how to address housing needs for today’s communities.




Flexible Imputation of Missing Data, Second Edition


Book Description

Missing data pose challenges to real-life data analysis. Simple ad-hoc fixes, like deletion or mean imputation, only work under highly restrictive conditions, which are often not met in practice. Multiple imputation replaces each missing value by multiple plausible values. The variability between these replacements reflects our ignorance of the true (but missing) value. Each of the completed data set is then analyzed by standard methods, and the results are pooled to obtain unbiased estimates with correct confidence intervals. Multiple imputation is a general approach that also inspires novel solutions to old problems by reformulating the task at hand as a missing-data problem. This is the second edition of a popular book on multiple imputation, focused on explaining the application of methods through detailed worked examples using the MICE package as developed by the author. This new edition incorporates the recent developments in this fast-moving field. This class-tested book avoids mathematical and technical details as much as possible: formulas are accompanied by verbal statements that explain the formula in accessible terms. The book sharpens the reader’s intuition on how to think about missing data, and provides all the tools needed to execute a well-grounded quantitative analysis in the presence of missing data.




Miss Smith and the Haunted Library


Book Description

A wonderful Halloween adventure with Miss Smith and her students Miss Smith's students know to expect the unexpected when she reads from her magical book. This time, Miss Smith takes her kids to the eerie library down the block and introduces them to the weird librarian, Virginia Creeper. But per usual, storytime is never ordinary when reading from Miss Smith's Incredible Storybook. And what starts out as a run-of-the-mill field trip soon becomes a full-out monster bash!







The Liberation of Consciousness from Identification with Form


Book Description

The purpose of this work is to explain in detail how consciousness identifies with form, how that identification is perpetuated by the reactivity that naturally follows, and why this misidentification is a necessary part of the evolution of consciousness into ever-greater awareness of itself. Ultimately, the reason for explaining all of this is to make it clear that the way out of this self-constructed and self-perpetuated delusion is through some degree of nonreactivity. That is, what will be explained is that the way out of what seems to be the trap in which we have purposefully placed ourselves lies simply through ceasing to continuously interact with the world in a way that is dictated solely by our delusion regarding our nature, i.e., by the idea that what we are is form. Because as long as we continue to interact with the world solely on the basis of this delusion, the delusion cannot do other than persist. And as long as the delusion persists, as long as we are actively generating and perpetuating this delusion through our reactivity, i.e., through the way in which we naturally tend to interact with the world of form while knowing ourselves as form, we must continue to know ourselves as we are not, and so we must also continue to suffer.




The Prevention and Treatment of Missing Data in Clinical Trials


Book Description

Randomized clinical trials are the primary tool for evaluating new medical interventions. Randomization provides for a fair comparison between treatment and control groups, balancing out, on average, distributions of known and unknown factors among the participants. Unfortunately, these studies often lack a substantial percentage of data. This missing data reduces the benefit provided by the randomization and introduces potential biases in the comparison of the treatment groups. Missing data can arise for a variety of reasons, including the inability or unwillingness of participants to meet appointments for evaluation. And in some studies, some or all of data collection ceases when participants discontinue study treatment. Existing guidelines for the design and conduct of clinical trials, and the analysis of the resulting data, provide only limited advice on how to handle missing data. Thus, approaches to the analysis of data with an appreciable amount of missing values tend to be ad hoc and variable. The Prevention and Treatment of Missing Data in Clinical Trials concludes that a more principled approach to design and analysis in the presence of missing data is both needed and possible. Such an approach needs to focus on two critical elements: (1) careful design and conduct to limit the amount and impact of missing data and (2) analysis that makes full use of information on all randomized participants and is based on careful attention to the assumptions about the nature of the missing data underlying estimates of treatment effects. In addition to the highest priority recommendations, the book offers more detailed recommendations on the conduct of clinical trials and techniques for analysis of trial data.




Missing Daughter


Book Description

When a twelve-year-old girl goes missing, a suburban family’s perfect life reveals its dark secrets in this tense psychological thriller. Life can change in an instant. For Ryan and Karen Lane, it happens on the morning they discover their twelve-year-old daughter’s window open, their beloved Maddie missing from her bed. Police investigate. Suspicions swirl. The Lane family is thrown into turmoil. Then detectives turn their sights on them. No one is ruled out. Not Karen, with her tragic past, who argued with her daughter. Not Ryan, with his violent streak. Not Maddie’s thirteen-year-old brother, Tyler, who heard voices in her room the night she vanished. As time goes by and no answers emerge, the Lanes fear that Maddie is gone forever. But when a stunning revelation shocks everyone, the family plunges deep into a world of buried secrets whose revelations threaten the very foundation of their lives.







From Data and Information Analysis to Knowledge Engineering


Book Description

This volume collects revised versions of papers presented at the 29th Annual Conference of the Gesellschaft für Klassifikation, the German Classification Society, held at the Otto-von-Guericke-University of Magdeburg, Germany, in March 2005. In addition to traditional subjects like Classification, Clustering, and Data Analysis, converage extends to a wide range of topics relating to Computer Science: Text Mining, Web Mining, Fuzzy Data Analysis, IT Security, Adaptivity and Personalization, and Visualization.





Book Description