Written by Grace Y. Yi , Statistical Analysis with Measurement Error or Misclassification, published by Springer Science Business Media LLC 2017.

Is a treasure of a book to go with a coding book. It gives the what, why and how of Missing data , Measurement error and Misclassification.

Chapter 2 covers Measurement error, incorrect readings of precise measurement. For example reading a three as an eight.

Systemic error, Sampling error, statistical bias, each type of error has it own way of handling it. And often the data contains more than on type of error.

Naive estimators incur larger bias than than estimators obtained from valid metrics but the later ones entail more variation than the naive estimators.

Lots to think about, Chapter 9 asks a lot of good questions.

Use the most plausible method to handle missing, mis classified and error prone data. The methods are well covered in the book.

This is a Stat’s book the key to the symbols is the beginning of the book.

It is know that ignoring measurement error can cause misleading results.