What To Do (and Not to Do) with Time-Series Cross-Section Data

What to do (and not to do) with Time-Series Cross-Section Data

T AlTe examine some issues in the estimation of time-series cross-section models, calling into 1/11 \ question the conclusions of many published studies, particularly in thefield of comparative T v political economy. We show that the generalized least squares approach of Parks produces standard errors that lead to extreme overconfidence, often underestimating variability by 50% or more. We also...

What To Do about Missing Values in Time-Series Cross-Section Data

Applications of modern methods for analyzing data with missing values, based primarily on multiple imputation, have in the last half-decade become common in American politics and political behavior. Scholars in this subset of political science have thus increasingly avoided the biases and inefficiencies caused by ad hoc methods like listwise deletion and best guess imputation. However, research...

Do We Know What We Do not Know? A Response to Celine Bonnet

Molecular approaches to diagnosis of invasive aspergillosis what we know and what we do not know.

Invasive aspergillosis (IA) are a major complication in immunocompromized patients where can be serious and rapidly fatal. Early diagnosis and early appropriate antifungal treatment is important in reducing mortality and morbidity. But despite many efforts to develop detection methods, the diagnosis of IA still remains challenging and current conventional methods are limited for adequate diagno...

Diagnostic and therapeutic challenges for dermatologists: What shall we do when we don’t know what to do?

What shall we do when we have done everything we could for the diagnosis and treatment of a patient, but were not successful? What shall we do when there is no definite treatment for a patient? What shall we do when we have no diagnosis or treatment for a patient? Some useful suggestions are presented here to get rid of these situations.