Difficulty: Proportion of correct answers
For more detailed item analyses we have to remove very extreme items (i.e., answered correctly by everybody or nobody).
items_not_extreme <- filter(items,
difficulty <= .99,
difficulty >= .01) %>%
.$item
scored_used_item_infos <- as.data.frame(scored[, items_not_extreme])For variable meanings see item.exam, except alpha_drop, which is Cronbach’s alpha of the full scale if this item were excluded.
## The determinant of the smoothed correlation was zero.
## This means the objective function is not defined.
## Chi square is based upon observed residuals.## The determinant of the smoothed correlation was zero.
## This means the objective function is not defined for the null model either.
## The Chi square is thus based upon observed correlations.## In factor.scores, the correlation matrix is singular, an approximation is used## Some items ( climate_avgPrecip climate_daysPrecip climate_storms sunstroke_thirsty sunstroke_cramp sunstroke_nausea sunstroke_tinnitus heatmeasures_shaderooms heatmeasures_proteinsugar heatmeasures_hotdrinks mmRain_10Kubik warning_sixhours thunderknowledge_death thunderknowledge_spring thunderstormmeasures_forest thunderstormmeasures_tree thunderstormmeasures_mobile thunderstormmeasures_soccer thunderstormmeasures_bike thunderstormmeasures_swim terms_vereinzelt terms_ortlich terms_vielerorts forecast_PPVa forecast_PPVb forecast_PODa forecast_PODc uvknowledge_time uvknowledge_latitude uvknowledge_ozon uvknowledge_clouds intensity_mountains intensity_water intensity_equator uvmeasures_noon uvmeasures_shade uvmeasures_exposure uvmeasures_cosmetic uvmeasures_windows windimpact_sturmisch windimpact_sturmSchwer windimpact_orkanartig windimpact_orkan ) were negatively correlated with the total scale and probably should be reversed. To do this, run the function again with the 'check.keys=TRUE' option## Joining, by = "item"The “fog” theme consists of only a single item and “slickness” only of two items; therefore they are not further analyzed.
## Some items ( climate_avgPrecip climate_daysWarm climate_avgTemp ) were negatively correlated with the total scale and probably should be reversed. To do this, run the function again with the 'check.keys=TRUE' option## Some items ( heatimpact_sweating sunstroke_nausea sunstroke_tinnitus heatmeasures_shaderooms heatmeasures_cooldrinks heatmeasures_hotdrinks heatmeasures_darkclothes heatmeasures_windows ) were negatively correlated with the total scale and probably should be reversed. To do this, run the function again with the 'check.keys=TRUE' option## Some items ( mmRain_onStreet ) were negatively correlated with the total scale and probably should be reversed. To do this, run the function again with the 'check.keys=TRUE' option## Some items ( thunderknowledge_freq thunderknowledge_death thunderknowledge_twice distance thunderstormmeasures_cower thunderstormmeasures_laydown ) were negatively correlated with the total scale and probably should be reversed. To do this, run the function again with the 'check.keys=TRUE' option## In factor.scores, the correlation matrix is singular, an approximation is used## Some items ( terms_ortlich terms_gebiet forecast_PPVa forecast_PPVb ) were negatively correlated with the total scale and probably should be reversed. To do this, run the function again with the 'check.keys=TRUE' option## Some items ( uvknowledge_temp uvknowledge_shade uvknowledge_snow intensity_hightemp intensity_cities intensity_spring intensity_southernhemis spf_50mal spf_50min spf_50mineverytime spf_50minlonger spf_brightskin spf_noTime uvmeasures_sunprotection uvmeasures_drinking uvmeasures_solarium uvmeasures_windows ) were negatively correlated with the total scale and probably should be reversed. To do this, run the function again with the 'check.keys=TRUE' option