Natural feeling domain-specific language for building structural equation models in R for estimation by covariance-based methods (like LISREL/Lavaan) or partial least squares (like SmartPLS)
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Error in as.POSIXlt.character(x, tz, ...) : character string is not in a standard unambiguous format" #352
I'm trying to resolve an issue while running estimate_pls() in RStudio. From browsing the internet, this error occurs when variables have dates. My data constructs don't have any dates in them. Both measurement and structural model load fine.
The data is coming from an SPSS SAV file, which I have loaded in a dataframe. I even extracted the data frame into an Excel file to reload the excel file in my data frame. I still get the same error.
Hello,
I'm trying to resolve an issue while running estimate_pls() in RStudio. From browsing the internet, this error occurs when variables have dates. My data constructs don't have any dates in them. Both measurement and structural model load fine.
The data is coming from an SPSS SAV file, which I have loaded in a dataframe. I even extracted the data frame into an Excel file to reload the excel file in my data frame. I still get the same error.
Thank you!
Here's part of my code after loading the data:
MM <- constructs( composite("MSR", single_item("MANIP_SR")), composite("CSR_Importance", multiitems(("CSRIMP"),1:13), weights = mode_B), composite("Psych_Contract", multiitems(("PSYCCON"), 1:9), weights = mode_B), composite("Affect_Commit", multiitems(("AFFECT"), 1:8), weights = mode_B), composite("Job_Satisfaction", multiitems(("CONTIN"),1:9), weights = mode_B), composite("Trust_Management", multiitems(("TRUSTINMG"),1:6), weights = mode_B), composite("JA", single_item(("JOB_AVAIL"))), composite("Turnover_intentions", multiitems(("TURNOVIN"),1:3)), interaction_term(iv = "Psych_Contract", moderator = "CSR_Importance", method = two_stage), interaction_term(iv = "TURN", moderator = "JA", method = two_stage))
turnover_intentions_sm_mod <- relationships( paths(from = c("MSR"), to = c("Psych_Contract")), paths(from = c("CSR_Importance", "Psych_Contract", "CSR_ImportancePsych_Contract"), to = c("Psych_Contract")), paths(from = c("Psych_Contract", "Job_Satisfaction"), to = c("Turnover_intentions")), paths(from = c("Psych_Contract", "Affect_Commit"), to = c("Turnover_intentions")), paths(from = c("Psych_Contract", "Trust_Management"), to = c("Turnover_intentions")), paths(from = c("JA", "Turnover_intentions", "JATurnover_intentions"), to = c("Turnover_intentions")) )
turnover_intentions_pls_model_mod <- estimate_pls ( data = csr, measurement_model = MM, structural_model = turnover_intentions_sm_mod, inner_weights = path_weighting, missing = mean_replacement, missing_value = "-99" )