How do you do expectation Maximisation?

The expectation-maximization algorithm is an approach for performing maximum likelihood estimation in the presence of latent variables. It does this by first estimating the values for the latent variables, then optimizing the model, then repeating these two steps until convergence.

How do you impute missing values in SPSS?

Analyze > Multiple Imputation > Impute Missing Data Values…

1. Select at least two variables in the imputation model.
2. Specify the number of imputations to compute.
3. Specify a dataset or IBM® SPSS® Statistics-format data file to which imputed data should be written.

What is EM in SPSS?

Using an iterative process, the EM method estimates the means, the covariance matrix, and the correlation of quantitative (scale) variables with missing values. Distribution. EM makes inferences based on the likelihood under the specified distribution. By default, a normal distribution is assumed.

Why is mean imputation bad?

3.1. Mean imputation (MI) is one such method in which the mean of the observed values for each variable is computed and the missing values for that variable are imputed by this mean. This method can lead into severely biased estimates even if data are MCAR (see, e.g., Jamshidian and Bentler, 1999).

What is Listwise deletion method?

In statistics, listwise deletion is a method for handling missing data. In this method, an entire record is excluded from analysis if any single value is missing.

How do you impute missing values?

The following are common methods:

1. Mean imputation. Simply calculate the mean of the observed values for that variable for all individuals who are non-missing.
2. Substitution.
3. Hot deck imputation.
4. Cold deck imputation.
5. Regression imputation.
6. Stochastic regression imputation.
7. Interpolation and extrapolation.

What is the best way to replace missing values in SPSS?

1. From the menus choose: Transform > Replace Missing Values…
2. Select the estimation method you want to use to replace missing values.
3. Select the variable(s) for which you want to replace missing values.

How is expectation maximization done in SPSS software?

To undertake expectation maximization, the software package, such as SPSS executes the following steps. First, the means, variances, and covariances are estimated from the individuals whose data is complete. In particular, the computer would generate the following information.

How to manage missing data in expectation maximization?

Choose Write a new data file. Press File and type a filename. Open this new file-which should include the data together with some of the missing data completed. To illustrate expectation maximization, consider the following extract of data. Missing values are observed for depression, age, and height. . . . . . . . . . .

How to estimate missing values in SPSS using EM?

Learn how to use the expectation-maximization (EM) technique in SPSS to estimate missing values . This is one of the best methods to impute missing values in SPSS. Category Education Show moreShow less Loading… Advertisement AutoplayWhen autoplay is enabled, a suggested video will automatically play next. Up next

Which is the best example of expectation maximization?

Tutorial on Expectation Maximization (Example) Expectation Maximization (Intuition) Expectation Maximization (Maths) 1 Stefanos Zafeiriou Adv. Statistical Machine Learning (course 495) • Assume that we have two coins, C1 and C2 • Assume the bias of C1 is ?1 (i.e., probability of getting heads with C1) • Assume the bias of C2 is ?2