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The SPSS user specifies which values -if any- must be excluded. User missing values are values that are invisible while analyzing or editing data. To assign for multiple variables: MISSING VALUES. To assign for a single variable: MISSING VALUES. I have seen something about user-defined missing values and I do not have much idea about it. In SPSS, 'missing values' may refer to 2 things: System missing values are values that are completely absent from the data. Values in a data set are missing completely at random (MCAR) if the events that lead to any particular data-item being missing are independent both of. NOTE: If you also want to specify what codes in your data signify that the data is missing ('Missing' column see above), add the following commands to your syntax. sub-command that allows users to specify a matrix. I need to know, if I need to use multiple imputation, then how can I avoid the imputation of the missing values due to the answer "no". SPSS users who have the Missing Values Analysis add-on module can obtain vectors of EM means and. So not all the missing values in these three variables (corresponding to the 4th, 5th and 6th question) are solely due to the answer "no" in the previous question. This example implies that all variables be numeric you cannot define numerical missing codes for string variables. All variables will have 0 as missing code. All variables will have value 0, as well as all values of 99 and above declared as missing.
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I should mention that some respondents didn't even answer the 3rd question and thus the answers to the 4th, 5th and 6th questions are automatically missing. MISSING VALUES AGEFATH AGEMOTH AGEBRO1 TO AGEBRO4 (0, 99 THRU HI).
#Spss code to define missing variables how to
I am sorry that I have no experience about how to make SPSS know that the missing values in the variables corresponding to the 4th, 5th and 6th question are due to the answer "no" in the previous (3rd) question. Simply put, data are missing when information that is present in variables for some cases is not present for. Only those who answered "yes" to the 3rd question are requested to answer the 4th, 5th and 6th question and those who answered "no" are requested to skip these three questions. Missing data are found in almost every dataset. Like, say, the 3rd question is a yes/no type question. I have a questionnaire that contains some skip questions.