example except for the file name. We can note which variables have which system missing values in SPSS: (.) blank Mplus text file and save as an input file (.inp). Here is such an ANALYSIS command: Full input file for basic analysis of free-formatted file hsb.dat. You can get the stata2mplus ado file by typing Notice the (nb) for negative binomial on the count statement. SAMPSTAT – sample statistics, including means, variances, skewness, kurtosis, minima and maxima, median and percentiles, and covariances and correlations, STD, STDXY, STDY – for standardized coefficients, CINTERVAL – confidence intervals for model parameters, TECH1 through TECH16 – the 16 TECH options output some of the details of the estimation procedure, such as starting values, covariance matrices of model parameters, and optimization (model fitting) history. Six months later, he came to us with a retinal detachment in the nasal area of the right eye. 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). Other then the ordered variable itself the setup is identical to These are the commands that you can enter into a A second option for formatting data files is fixed format, where variables occupy fixed positions in the data file (e.g. the binary probit model. Count data often use exposure variables to indicate the number of times the event could have happened. For example, if -999 is the value used in coding missing values, then the previous example’s code would be amended with a Missing statement in the Variable: block indicating this. Here is the Stata command to load and convert the Stata dataset hsb2.dta to Mplus. Most data files will be in this format. For most free-formatted files, the entirety of the DATA command will be the location of the data file. For information on interpreting the results of logistic models, please visit Annotated Output: Logit Regression . The. creating dummy variables for a categorical variable), ANALYSIS – technical details of the analysis (estimator, algorithm), OUTPUT – any additional output not produced by default by running the statistical model, SAVEDATA – save analysis data and some analysis results, PLOT – generate graphics of data or analysis results. Number of observations 118 . 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. Again, after saving and running this input, you can check the output to see if  “INPUT READING TERMINATED NORMALLY” appears. 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. If you do not have devtoolsinstalled, first install it and then install MplusAutomation. These are followed by one variable of length one (F1.0), then two of length 2 and one of length 1 (2F2.0, F1.0). The next model in this section is a negative binomial regression model. predictor female. By default, Mplus uses restricted maximum likelihood (MLR), so robust standard errors would be given in the output. The OUTPUT command is used to request additional output not normally produced by the analysis specified in ANALYSIS and MODEL. 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. ;), CENSORED, NOMINAL, CATEGORICAL, and COUNT to specify dependent variables that fit one of those types, STRATIFICATION, CLUSTER, and WEIGHT to variables reflecting complex or clustered sampling, GROUPING to specify a grouping variable for multi-group analyses. In our dataset, we can see that different variables have different values for missing. After the command and colon, we specify code and options for that command. indicated in the output below). 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. 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 was used for these examples. Next we have a logistic regression model. 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. We will be exploring several different MODEL commands to specify different classes of models throughout the seminar. The zero-inflated models are examples of multiple equation models. good first check that your data were read in successfully. All statements must end with a semicolon. The .inp file contains more detail about the data file than our earlier examples; however, all of the same command blocks are present. It is worth noting that this missing data approach is available for all of the different regression models, not just for the OLS regression. Mplus cannot handle string variables; such variables should be removed from the data file or converted to numeric before values 1, 2 and 3. dataset name hsb2.dat and  hsb2.inp. There are a few notes to make before summarizing the most used operations under the DEFINE command. In context, a regression command looks like this: For most of the examples we will be using the hsbdemo.dat dataset. A SUMMARY OF THE Mplus LANGUAGE. Mplus is not case sensitive. converting the data set to Mplus. USEOBSERVATIONS to select a subest of observations to use, MISSING to specify values that signify missing (e.g. You will also note that the output contains a set of parameter estimates for each equation. 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. Other settings for TYPE include TYPE=MIXTURE for categorical latent variable models, and TYPE=TWOLEVEL or TYPE=THREELEVEL for multilevel models. The first model in this section is a poisson regression model using awards as the ), Factor analysis, exploratory and confirmatory, Mixture models (latent class, latent profile, etc. The DATA and VARIABLES command blocks are required. Variables generated in the DEFINE command must be listed in the USEVARIABLES option of the VARIABLES command and must be listed after the variable transformed to create the new variable. to 8 characters. numbers and/or the underscore character (_). with a semi-colon. Zero-inflated negative binomial regression. Use the missing option of stata2mplus to specify a missing value code. We will discuss further checks in the next section.44, Full input file for basic analysis of fixed-formatted file fixed.dat. 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. The setup for this model parallels that of the zero-inflated poisson model above. To obtain standard errors calculated using maximum likelihood, include the analysis: estimator = ml; block. This chapter contains a summary of the commands, options, and settings of the Mplus language. By default however, Mplus does not allow for missingness on exogeneous variables (x-variables) in Mplus. It stores both in the current For each command, default settings are found in the last column. USEOBSERVATIONS to select a subest of observations … 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. Mplus provides several mathematical and logical operators, as well as options to transform variables in many ways. 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 I wanted to aggregate those 358 to 61 observations. By default, Mplus expects a free-formatted data file. The program stata2mplus can also convert missing values in Stata to missing values codes in the Mplus data file (e.g. SPSS FAQ: How can I move my data from SPSS to Mplus? Variable names can be no longer than 8 characters; if your variable names are longer than 8 characters, they will be truncated Check your data and format statement. You can download the dataset by clicking here. The non-bias-corrected bootstrap approach will generally produce preferable confidence limits and standard errors for the indirect effect test (Fritz, Taylor, & MacKinnon, 2012). Missing values cannot be represented by blank spaces in free format. The code from the input file created appears below. Files formatted in this way were more commonly encountered in the past. For our first Mplus syntax file, we will be using TYPE=BASIC, which estimates descriptives such as means, variances, and correlations. For information on interpreting the results of zero-inflated poisson models models, please visit Annotated Output: Zero-inflated Poisson Regression. A 44-year-old man with high myopia and right optic neuritis history complained of visual impairment due to cataract in the right eye. – To select observations – USEOBSERVATIONS ARE DemEver EQ 0; – Equal (EQ, ==), Not Equal (NE, /=), Greater than or equal to (GE, >=), Less than or equal to (LE, <=), greater than (GT, >), less than (LT, <), AND, OR, NOT • USEVARIABLE ARE – Variables included in analysis – … Model 1 A text file (of the faculty data) with the data ready for use in Mplus can be downloaded here. However, I have been doing some reading around R, which I have been … generate expected classifications of observations based upon the characteristics of your specified model. Mplus VERSION 8 Command and option names can be shortened to their first four letters. The maximum length of any line in an Mplus input file is 90 characters (80 characters in older versions of Mplus). to read in the data. working directory in Stata (use the command pwd to get the path) with the Negative binomial models are useful when there is overdispersion in the data. For this next model we use an ordered response variable, ses, which takes on the Below, we use hsbmis.csv. This is a MODEL FIT INFORMATION . Mplus can be used to estimate a model in which some of the variables have missing values using full information maximum likelihood (FIML). You can download the data by clicking here. -9999). The reason is that for some parts of some of the output, Mplus will add one or two additional characters (e.g. Perhaps its greatest strengths are in its capabilities to model latent variables, both continuous and categorical, which underlie its flexibility. Each command option specification is separated by a semicolon (;). The Main Model . Thus, the estimate for female of 0.214 is for the count equation, and the estimate -4.029 is for the excess zero equation. the continuous variables read and math as predictors along with the binary For the ordered logit model we again use the maximum likelihood estimator. Note that Mplus will save output in an output file with the same name as an input file. 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…) 2.3. Observations. All the files for this portion of this seminar can be downloaded here. The variables in the file are id, female, race, ses, schtyp, prog, read, write, math, science and socst. The model results near the bottom show estimates and standard errors that are close to the first model with complete data. The ANALYSIS command block is included so that we can check the data. ), Department of Statistics Consulting Center, Department of Biomathematics Consulting Clinic. Hence it has to look like this. (lavaan does not exclude cases I have 358 observations on IV and Mediators. 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. However, for some models, Mplus drops cases with missing values on any of the predictors. To change it, you can use the Stata’s cd command. Mplus will output all solutions from smallest n to largest n factors extracted. Mplus also has extensive Monte Carlo simulation capabilities to generate data from statistical analyses and to perform power analyses. The Mplus .inp file is saved in the current working directory, which is listed in the lower left-hand corner of the Stata window. The symbol “=” and keywords “IS” and “ARE” can be used interchangeably in most commands (not in DEFINE, MODEL TEST or MODEL CONSTRAINT). 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. Model Specification, the MPlus input file Should you use Mplus? count response variable. 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. We begin by showing the input file which we called hsbreg.inp. The ANALYSIS command specifies the technical details of the statistical analysis, such as the type of analysis, the estimator and the algorithm used. We will begin with a probit regression model. Should you use Mplus to perform EFA, CFA, and SEM analyses on your data? Comments can be added to the Mplus syntax by starting the line with an exclamation point (!). 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). Mplus (output excerpts) Mplus VERSION 6.12 . However, you can use a maximum of 500 variables for Mplus analysis. 4.1 install the “rhdf5” package to read gh5 files; 4.2 load packages; 4.3 Keyboard shortcuts; 5 - Read in data; 6 - A couple ways to explore & view data in R; 7 - View dataframe with labels & response scale meta-data. You can incorporate exposure into your model by using the exposure() option. Institute for Digital Research and Education. USEVARIABLES (often shortened to usevars) to select a subset of the variables to use in the analysis. Notice the (p) for poisson on the count statement. Although we are using the same predictors in both equations, this is not necessary. By default, Mplus will use all of the variables in the data set. The first row of a data file in Mplus has to be the first line of data, so NO variable names above! After “DATA:”, specify “file is” (or “file = “) and then the name of the file. Mplus recognizes that honors has two levels. 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. (b) rotation = name(type) name specifies the family of rotations to be used and type relates to oblique or orthogonal. We again use the maximum likelihood estimator but declare prog to be a nominal variable. Next, we will take a look at the output file, hsbreg.out. My DV has 61 observations. Fret not, Mplus has your back with the DEFINE command. The statistical modeling program Mplus Version 8.2 is featured with all models updated. By default, Mplus will use all of the variables in the data set. The keyword for regression models is on, as in response variable regressed on predictor1, predictor2, etc. *** ERROR The number of observations is 0. MISSING ARE . regression models, path analysis, CFA, SEM and latent growth models with continuous latent variables). 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. Variable names can contain 2.1 Tools we will use in lab; 3 - Creating an R-Project; 4 - Installing & loading packages. Examples of these model is beyond the scope of this seminar. Note: In Mplus, there is no limit on the number of observations or number of variables in the data set to be read in. The final model in this section is a zero-inflated negative binomial regression model. In Mplus, you will need to explicitly list out the values that represent missing data. The code from the input file created appears below. See our Annotated Output: Ordinary Least Squares Regression page for more detailed interpretations of each model parameter. The example below contains the first 20 lines from a file called hsb.dat. needed to read the dataset into Mplus are created. Among the many models Mplus can fit are: Additionally, Mplus can fit most of the models above to complex survey data as well as data that contain missing values or from multiply imputed data. Notice the (pi) for zero-inflated poisson on the count statement. If a statement needs more than 90 characters, break the statement up into multiple lines, ending the statement (not each line) In this example we will boldface the line that specifies the regression analysis. 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. 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. Starting with Mplus 5, the default analysis type allows for analysis of missing data by full information maximum likelihood (FIML). H0 Value -757.201 . identify them as being part of the Mplus code. 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. ... Use cut instead of delete and paste this line of variables in Mplus, in this way mistakes are much less likely! The codebook for the data is given below. 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. The Mplus User’s Guide is the reference manual for Mplus. Dummy variables must be created for any categorical, BY is used to indicate indicators for latent variables. The TITLE command is optional and specifies a title used for the output file. 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”. Mplus requires data to be read in from a text file without variable names, with numeric values only, and with missing data coded as a single numeric value, such as -999. For the rest of this section we will present only the input files for each of the models. Institute for Digital Research and Education. Some portions of the output were deleted to save paper. ), 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. A common workflow for preparing data to analyze in Mplus is to perform the … Write your own input program (it is relatively easy). for female , -9 for race , -99 for ses , -999 for schtyp , -9999 for read , and -99999 for write . In this seminar, we will learn some basic Mplus syntax which will empower you to use Mplus on your own. 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”. However, in many examples of Mplus code, the Mplus commands and options are in capital letters to convert a Stata dataset to an Mplus ASCII data file plus the necessary commands (in an Mplus input file) To change it, you can use the Stata’s cd command. 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. Variable names must start with an alphabet character (i.e., a letter of the alphabet). If you are an SPSS user, you can prepare your data to be read into Mplus with a few steps detailed in SPSS FAQ: How can I move my data from SPSS to Mplus?. 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. variable 1 is first 2 column, variable 2 is column 3, variable 3 is columns 4 through 6, etc.). Note that in order to use these files, you will have to adjust file names and locations, as well as the number of observations per data set and the number of data sets. To run an analysis in Mplus, 2 files are needed: Mplus creates an output file for each input file that is run. 1a Saving Data Files for Use in Mplus Commands and options can be shortened to four or more letters. in a semicolon. Starting in version 5 this is done by default, in earlier versions this type of estimation could be requested using type = missing;. Mplus can also run zero-truncated negative binomial models and negative binomial hurdle models. 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. Even with these adjustments, this will NOT reproduce our results exactly, because no random seed is set. For information on interpreting the results of poisson models, please visit Annotated Output: Poisson Regression. Notice the (nbi) for zero-inflated negative binomial on the count statement. INPUT INSTRUCTIONS . The default is also to report the conventional chi-square test and maximum likelihood standard errors. 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. The input file for this example is identical to the previous The difference between this model and the probit model is that we specify that maximum likelihood is to be used as the estimator. 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. The Mplus User’s Guide can be found on the Mplus website. A .dat file containing the dataset and the input file The line does not need to be ended This matches what we see in the codebook. 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. 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. I have been advised by my one of my supervisors to use Mplus for the analysis. 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! The first observation is a list of variables names rather than data. Mplus is a highly flexible, powerful statistical analysis software program that can fit an extensive variety of statistical models using one of many estimators available. The next model is a zero-inflated poisson regression model. 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. In our first example we will use a standardized test, write, as the response variable and Number of Free Parameters 12 . It contains a nice collection of continuous, binary, ordered, categorical and count variables. For information on interpreting the results of multinomial logistic models, please visit Annotated Output: Multinomial Logistic Regression. In the VARIABLE command, which is required, we specify the names of the variables and any information about them that Mplus needs to know to run the statistical analysis. MUTHEN & MUTHEN . 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. search stata2mplus in the Stata command window and following the directions that are given. For information on interpreting the results of probit models, please visit Annotated Output: Probit Regression. 1 - Lab outline; 2 - Preparing to work with MplusAutomation. 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. 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! 02/08/2012 4:03 PM . We performed uneventful phacoemulsification and implanted a Toric Lentis Mplus IOL in his right eye. Mplus treats this as a probit model because we declare that honors is a categorical variable. To convert the file to mplus, start mplus and run the file hsb2.inp. Here you can see the variables are separated by commas, and the variable names are not on the first line. 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;). Loglikelihood . Author(s) Joshua F. Wiley See Also readModels Mplus (output excerpts) Note: I use the bootstrap approach here for testing the indirect effect. It is based, in part, on the likelihood function and it is closely related to the Akaike information criterion (AIC).. Here is an example of using the DEFINE command to create a new variable “highmath” that is a dichotomized version of variable math, and the accompanying VARIABLE command with the USEVARIABLES option: The MODEL command specifies the statistical model to be estimated. 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). 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. This code will appear in the MISSING option of the VARIABLES command of the input file created by stata2pmlus. Number of observations 275 . The Mplus .inp file is saved in the current working directory, which is listed in the lower left-hand corner of the Stata window. ), Longitudinal analysis (latent transition analysis, growth mixture models, etc. For every analysis, Mplus requires that the names of the variables be specified in the order that they appear in the data file. You can incorporate exposure into your model by using the exposure() option. ), Department of Statistics Consulting Center, Department of Biomathematics Consulting Clinic, Annotated Output: Ordinary Least Squares Regression, Annotated Output: Multinomial Logistic Regression, Annotated Output: Zero-inflated Poisson Regression. 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. Regression models (linear, logistic, poisson, Cox proportional hazards, etc. Note that Mplus uses a weighted least squares with missing values estimator (as List the variable names after “names are” (or “names = “). It contains detailed information about all of the input file commands, as well as numerous examples of a huge variety of models, with code and explanation for each example.