mplus use observations

 

For the multinomial logit model we use the variable prog, which indicates the type of high school program, where 1 is general, 2 is academic and 3 is vocational. The Mplus input file contains all of the commands to read the data file properly, run the statistical analysis, and to produce any graphs or additional output. The. For this next model we use an ordered response variable, ses, which takes on the Up near the beginning of the output there is a table that shows the proportion of data present for each of the covariates in the model. Mplus has a rich collection of regression models including ordinary least squares (OLS) regression, probit regression, logistic regression, ordered probit and logit regressions, multinomial probit and logit regressions, poisson regression, negative binomial regression, inflated poisson and negative binomial regressions, censored regression and censored inflated regression. Other settings for TYPE include TYPE=MIXTURE for categorical latent variable models, and TYPE=TWOLEVEL or TYPE=THREELEVEL for multilevel models. To obtain standard errors calculated using maximum likelihood, include the analysis: estimator = ml; block. Should you use Mplus to perform EFA, CFA, and SEM analyses on your data? In Mplus, when measured exogenous variables (but not indicators for exogenous latent variables) have missing values, the cases with missing dataare excluded from the analysis. The OUTPUT command is used to request additional output not normally produced by the analysis specified in ANALYSIS and MODEL. Below, we use hsbmis.csv. Important requirements for any Mplus data file: By default, Mplus excepts data files in “free format”, where the values for each of the variables are separated by a delimiter, which must be a comma, space or tab. Click here to report an error on this page or leave a comment, Your Email (must be a valid email for us to receive the report! Other then the ordered variable itself the setup is identical to dataset name hsb2.dat and  hsb2.inp. Most data files will be in this format. For information on interpreting the results of logistic models, please visit Annotated Output: Logit Regression . Examples of these model is beyond the scope of this seminar. Three important keywords (options) are used in the MODEL command to specify relationships among variables: For example, if we wanted to define a latent variable representing academic prowess that is measured by 5 test score variables, we could specify (we would also need to add an ANALYSIS command with TYPE=GENERAL): The MODEL command is technically optional, but almost always specified unless we only want descriptive statistics (ANALYSIS: TYPE=basic;). to read in the data. MODEL FIT INFORMATION . When I use Proc Export for creating a MPLUS data set I have to open the data set with notepad, delete the first observation in the file and save it before MPLUS can read it. In context, a regression command looks like this: For most of the examples we will be using the hsbdemo.dat dataset. Command and option names can be shortened to their first four letters. My DV has 61 observations. The input file for this example is identical to the previous Here you can see the variables are separated by commas, and the variable names are not on the first line. Comments can be added to the Mplus syntax by starting the line with an exclamation point (!). Here is the VARIABLE command for the free-formatted file hsb.dat: Other options we can specify in the VARIABLE COMMAND: Further advice for using the VARIABLES command. in a semicolon. In this seminar, we will learn some basic Mplus syntax which will empower you to use Mplus on your own. Mplus will look for the data file in the same directory as where you save the input file, but you can place them in diferrent directories by specifying a full path for the data file. Each command option specification is separated by a semicolon (;). MISSING ARE . Some options for additional output: For example, to request all of the sample statistics available, we can specify this OUTPUT command: If you are a Stata user, a user-written a command, stata2mplus, will Titles can contain any combination of characters and numbers (except for the name of an input file section with a colon, for example “DATA:”), and do not need to terminate in a semicolon. Starting from the hsb2.sav dataset, once you have created a .csv file, hsb2.csv, without variable names, the code below can read in your data. Again, after saving and running this input, you can check the output to see if  “INPUT READING TERMINATED NORMALLY” appears. By default, Mplus will use all of the variables in the data set. It stores both in the current We will discuss further checks in the next section.44, Full input file for basic analysis of fixed-formatted file fixed.dat. Write your own input program (it is relatively easy). For information on interpreting the results of multinomial logistic models, please visit Annotated Output: Multinomial Logistic Regression. By default, Mplus expects a free-formatted data file. Mplus cannot handle string variables; such variables should be removed from the data file or converted to numeric before Observations. Mplus can also run zero-truncated negative binomial models and negative binomial hurdle models. In this example we will boldface the line that specifies the regression analysis. There are a few notes to make before summarizing the most used operations under the DEFINE command. Here is a DATA command for the fixed formatted file fixed.dat above: On the format statement, 3F2.0 indicates that the file begins with three variables each of length two. Although we are using the same predictors in both equations, this is not necessary. (lavaan does not exclude cases Note that the total number of variables is now back up to 200 instead of 76 (200-124=76) had we not imputed the mean of the x-variables. Notice the (p) for poisson on the count statement. Here are the commonly used commands (required sections are bolded): Place a colon (:) after the name of the command in the input file so Mplus will recognize it as a command. •Or use Mplus’ shortcut – Intercept slope | time1@0 time2@1 time3@2 time4@3; –Assumes intercept is í’s all around –Creates paths you specify for slope –Allows intercept and slope to correlate –Sets variable intercepts to 0 so that all prediction is in the mean of the latent variables (Intercept and Slope) A 44-year-old man with high myopia and right optic neuritis history complained of visual impairment due to cataract in the right eye. You can get the stata2mplus ado file by typing You can incorporate exposure into your model by using the exposure() option. search stata2mplus in the Stata command window and following the directions that are given. Here is a TITLE section for the freely formatted file hsb.dat above: The DATA command is required and contains the location of the data file and information about how it is formatted. Notice the (nbi) for zero-inflated negative binomial on the count statement. Starting with Mplus 5, the default analysis type allows for analysis of missing data by full information maximum likelihood (FIML). However, I have been doing some reading around R, which I have been … H0 Value -757.201 . We did not use the DEFINE, MODEL, or OUTPUT commands for our first Mplus file, but below is some basic information about each of them: The DEFINE command is used to generate new variables that are not found in the data set. Mplus provides several mathematical and logical operators, as well as options to transform variables in many ways. Thus, the estimate for female of 0.214 is for the count equation, and the estimate -4.029 is for the excess zero equation. In this case, there is one equation for the count model, awards on female read math, and a second equation for estimating the excess zeros, awards#1 on female read math; this is a logit model. It is based, in part, on the likelihood function and it is closely related to the Akaike information criterion (AIC).. ... Use cut instead of delete and paste this line of variables in Mplus, in this way mistakes are much less likely! We can note which variables have which system missing values in SPSS: (.) We performed uneventful phacoemulsification and implanted a Toric Lentis Mplus IOL in his right eye. The code from the input file created appears below. the continuous variables read and math as predictors along with the binary We begin by showing the input file which we called hsbreg.inp. The ANALYSIS command block is included so that we can check the data. You can download the dataset by clicking here. Model 1 A text file (of the faculty data) with the data ready for use in Mplus can be downloaded here. By default however, Mplus does not allow for missingness on exogeneous variables (x-variables) in Mplus. It provides researchers with a flexible tool that allows them to analyze data with an easy-to-use interface and graphical displays of data and analysis results. By default, Mplus will use all of the variables in the data set. good first check that your data were read in successfully. The statistical modeling program Mplus Version 8.2 is featured with all models updated. I have 358 observations on IV and Mediators. Each line of comment must start with an exclamation point. No statistical model is fit. Zero-inflated negative binomial regression. Here is a DATA command for the freely formatted file hsb.dat above: Fixed format data are handled using a Fortran-type format statement in the data command block. identify them as being part of the Mplus code. Variable names can be no longer than 8 characters; if your variable names are longer than 8 characters, they will be truncated Use the missing option of stata2mplus to specify a missing value code. The TITLE command is optional and specifies a title used for the output file. Either a data frame of class ‘mplus.model.coefs’, or in the case of multiple group models, a list of class ‘mplus.model.coefs’, where each element of the list is a data frame of class ‘mplus.model.coefs’, or a named vector of coefficients, if raw=TRUE. Mplus VERSION 8 Number of observations 118 . Next we have a logistic regression model. Hence it has to look like this. The ANALYSIS command is optional, and if the default settings for the options are appropriate for the analysis (see the Mplus User’s Guide for defaults), then can be skipped. This code will appear in the MISSING option of the VARIABLES command of the input file created by stata2pmlus. Model Specification, the MPlus input file For information on interpreting the results of poisson models, please visit Annotated Output: Poisson Regression. If you change a model and want to save a new output file, save the changed input file under a new name or your original output will be over written. Mplus can be used to estimate a model in which some of the variables have missing values using full information maximum likelihood (FIML). If your SPSS data file contains missing data, complete the same steps you would for SPSS data without missing values, but note the values used for missing values. In statistics, the Bayesian information criterion (BIC) or Schwarz information criterion (also SIC, SBC, SBIC) is a criterion for model selection among a finite set of models; the model with the lowest BIC is preferred. Number of observations 275 . In order to force Mplus to use all observations, we can estimate the mean of the x-variables so that the x-variables becomes an endogenous variable in Mplus and gets treated as an imputable variable. generate expected classifications of observations based upon the characteristics of your specified model. Starting in version 5 this is done by default, in earlier versions this type of estimation could be requested using type = missing;. The first observation is a list of variables names rather than data. ), A data file (often using a .dat extension), An input file containing a set of commands to analyze the data file (usually .inp extension), no variable names at the top of the file; first row should be data, DEFINE – used to generate new variable not found in the data file (e.g. 1 - Lab outline; 2 - Preparing to work with MplusAutomation. After saving and running the .inp file, you can look in the output file for “INPUT READING TERMINATED NORMALLY” appearing below the entered code. Mplus is not case sensitive. For our first Mplus syntax file, we will be using TYPE=BASIC, which estimates descriptives such as means, variances, and correlations. This opens by default after the analysis has been run, and it has the same name as the input file (but has an .out extension). blank Mplus text file and save as an input file (.inp). If a statement needs more than 90 characters, break the statement up into multiple lines, ending the statement (not each line) indicated in the output below). Count data often use exposure variables to indicate the number of times the event could have happened. The code from the input file created appears below. Perhaps its greatest strengths are in its capabilities to model latent variables, both continuous and categorical, which underlie its flexibility. To change it, you can use the Stata’s cd command. Mplus also has extensive Monte Carlo simulation capabilities to generate data from statistical analyses and to perform power analyses. There are many ways read your data into Mplus: Use Stattransfersoftware (available in BA B-18 on the same machine with Mplus) – seems to work ok, but you still may need additional preparation (be careful with missing and character values). To convert the file to mplus, start mplus and run the file hsb2.inp. Zero-inflated models are useful when there is a second mechanism generating zeros, such that there would be many more zeros than would be expected from the count model alone. ), Factor analysis, exploratory and confirmatory, Mixture models (latent class, latent profile, etc. variable 1 is first 2 column, variable 2 is column 3, variable 3 is columns 4 through 6, etc.). Even with these adjustments, this will NOT reproduce our results exactly, because no random seed is set. These are the commands that you can enter into a Note that the total number of variables is now back up to 200 instead of 76 (200-124=76) had we not imputed the mean of the x-variables. (b) rotation = name(type) name specifies the family of rotations to be used and type relates to oblique or orthogonal. ), Department of Statistics Consulting Center, Department of Biomathematics Consulting Clinic. The program stata2mplus can also convert missing values in Stata to missing values codes in the Mplus data file (e.g. In order to force Mplus to use all observations, we can estimate the mean of the x-variables so that the x-variables becomes an endogenous variable in Mplus and gets treated as an imputable variable. Loglikelihood . I wanted to aggregate those 358 to 61 observations. Mplus treats this as a probit model because we declare that honors is a categorical variable. Here is the Stata command to load and convert the Stata dataset hsb2.dta to Mplus. in the case of thresholds); and if your variable name has eight characters, the last two characters will be truncated and replaced by the new characters.> Operations with the DEFINE command can be done on all observations or a selection of some based on conditional statements (e.g., IF(gender EQ 1) THEN…) You can download the data by clicking here. The FIML approach uses all of the available information in the data and yields unbiased parameter estimates as long as the missingness is at least missing at random. The symbol “=” and keywords “IS” and “ARE” can be used interchangeably in most commands (not in DEFINE, MODEL TEST or MODEL CONSTRAINT). A common workflow for preparing data to analyze in Mplus is to perform the … To run an analysis in Mplus, 2 files are needed: Mplus creates an output file for each input file that is run. The TYPE option for the ANALYSIS command is set to “general” by default, which is appropriate for a large variety of models which estimate relationships between observed variables and continuous latent variables (e.g. After the command and colon, we specify code and options for that command. Mplus (output excerpts) Note: I use the bootstrap approach here for testing the indirect effect. Note that for certain models if you specify variables under USEVARIABLES and don’t include them in the model, you will get a warning that the “Variable is uncorrelated with all other variables”. The Mplus .inp file is saved in the current working directory, which is listed in the lower left-hand corner of the Stata window. Notice the (nb) for negative binomial on the count statement. Count data often use exposure variables to indicate the number of times the event could have happened. Six months later, he came to us with a retinal detachment in the nasal area of the right eye. predictor female. Note: In Mplus, there is no limit on the number of observations or number of variables in the data set to be read in. Commands and options can be shortened to four or more letters. count response variable. List the variable names after “names are” (or “names = “). Files formatted in this way were more commonly encountered in the past. needed to read the dataset into Mplus are created. The first model in this section is a poisson regression model using awards as the For each command, default settings are found in the last column. Next, we will take a look at the output file, hsbreg.out. The Mplus User’s Guide is the reference manual for Mplus. USEVARIABLES (often shortened to usevars) to select a subset of the variables to use in the analysis. Mplus will by default use maximum likelihood estimation (specifically, Full Information Maximum Likelihood, or FIML, which is robust to data that have values missing at random). Number of Free Parameters 12 . You can install the latest release of MplusAutomation directly fromCRANby running Alternately, if you want to try out the latest developmentMplusAutomation code, you can install it straight from github usingHadley Wickham's devtools package.