Αποτελέσματα Αναζήτησης
How can I replace missing values with previous or following nonmissing values or within sequences? 1. The problems. Users often want to replace missing values by neighboring nonmissing values, particularly when observations occur in some definite order, often (but not always) a time order.
This presentation focuses on how to implement two of these methods Stata. Multiple Imputation (MI) Full information maximum likelihood (FIML) Other principled methods have been developed, for example Bayesian approaches and methods that explicitely model missingness.
MI is a simulation-based approach for analyzing incomplete data that involves filling in missing responses multiple times. MI is often regarded as the most flexible missing data approach. It can be used with virtually any analysis model. The imputation model can include auxiliary variables.
22 Σεπ 2023 · This column focuses on the easiest problems in which a researcher is clear, or at least highly confident, about what missing values should be instead, implying a deterministic replacement. The main tricks are copying values from observation to observation and using the ipolate command.
4 Δεκ 2018 · i have a set of data (n=586) with 29 variables. in some of the variables i have 2 to 3% missing values. what is the code to replace the missing data by mean or median for all variables at once. thanks in advance
2 Σεπ 2020 · I've looking to change all the zeroes in a varlist to missing values. I think I first need to convert the values to string first and have tried to use tostring however it says that the varlist cannot be converted reversibly; what does this mean and is there a better way to do this?
15 Απρ 2021 · What I would add is that you have to diagnose the mechanism underlying your missing data (MCAR; MAR; MNAR). See -mi- entry for further details and interesting references.
