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Estoy analizando el análisis de confiabilidad de una variable. Los ítems están codificados con 0 (error) y 1 (acierto), en uno de los ítems todos los participantes acertaron, por lo que JASP no me analiza ese ítem porque lo señala como error. Cómo puedo solucionarlo????

• I'll ask our expert, Don.

@Don: Google translate the above text gives:

"I'm analyzing the reliability analysis of a variable. The items are coded with 0 (error) and 1 (hit), in one of the items all the participants were right, so JASP does not analyze that item because it indicates it as an error. How can I solve that????"

Cheers,

E.J.

• Unfortunately, there is no way to compute the reliability for an item with zero variance. If you try this in R, you get the following:

```library(psych)
df <- data.frame(x = rnorm(10), y = rnorm(10), z = 1)
var(df\$z) # no variance
[1] 0

alpha(df)
Some items ( x ) 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
Reliability analysis
Call: alpha(x = df)

raw_alpha std.alpha G6(smc) average_r   S/N  ase  mean   sd median_r
-0.55     -0.65   -0.24     -0.24 -0.39 0.86 -0.31 0.66    -0.24

lower alpha upper     95% confidence boundaries
-2.24 -0.55 1.14

Reliability if an item is dropped:
raw_alpha std.alpha G6(smc) average_r S/N alpha se var.r med.r
x     -0.24     -0.24    0.06     -0.24  NA       NA -0.24 -0.24
y      0.06     -0.24      NA        NA  NA       NA  0.06 -0.24

Item statistics
n raw.r std.r r.cor r.drop  mean   sd
x 10  0.82  0.61   NaN  -0.24 -0.38 1.27
y 10  0.35  0.61   NaN  -0.24 -0.25 0.76
Warning messages:
1: In alpha(df) : Item = z had no variance and was deleted
2: In alpha(df) :
Some items 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
3: In matrix(unlist(drop.item), ncol = 10, byrow = TRUE) :
data length [16] is not a sub-multiple or multiple of the number of columns [10]
4: In sqrt(Vtc) : NaNs produced
```

The first warning message is:

```1: In alpha(df) : Item = z had no variance and was deleted
```

JASP throws an error rather than deleting the items with a warning. If you still want to do a reliability analysis on the remaining items, I'd suggest deleting items with zero variance.

• OK, thank you