> model.sem <- ' + ###Measuremement models + Malnutrition =~ WAZ + HAZ +WAH + Immediate_causes =~ morb + month_bf + num_semifood + Underlying_causes =~ bmi + birth_weight + bord + Basic_causes =~ HH_members + w_index +m_educa + + ### Regression + + Malnutrition ~ Immediate_causes + Underlying_causes + Basic_causes + Immediate_causes ~ Underlying_causes + Basic_causes + Underlying_causes ~ Basic_causes + + ###Residual correlation + WAZ ~~ HAZ + WAH + morb ~~ month_bf + num_semifood + bmi ~~ birth_weight + bord + HH_members ~~ w_index + m_educa + ' > fitsem <- sem(model.sem, data=data4R, missing = "listwise") Error in lav_data_full(data = data, group = group, cluster = cluster, : lavaan ERROR: missing observed variables in dataset: num_semifood
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fitsem <- sem (model.sem, data=data4R) Warning messages: 1: In lav_data_full(data = data, group = group, cluster = cluster, : lavaan WARNING: some observed variances are (at least) a factor 1000 times larger than others; use varTable(fit) to investigate 2: In lav_model_vcov(lavmodel = lavmodel, lavsamplestats = lavsamplestats, : lavaan WARNING: could not compute standard errors! lavaan NOTE: this may be a symptom that the model is not identified. 3: In lav_object_post_check(object) : lavaan WARNING: some estimated ov variances are negative