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Project measure / variable:   Brown2   rev_err_d4

ID, description, units MPD:22514   rev_err_d4   reversal training mean errors   [n]  day4  
Data set, strains Brown2   inbred   13 strains     sex: both     age: 10-18wks
Procedure Barnes circular maze
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  STRAIN COMPARISON PLOT
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Brown2 - reversal training mean errors day4



  MEASURE SUMMARY
Measure Summary FemaleMale
Number of strains tested13 strains13 strains
Mean of the strain means6.75   n 7.04   n
Median of the strain means6.25   n 5.70   n
SD of the strain means± 2.45 ± 3.35
Coefficient of variation (CV)0.364 0.476
Min–max range of strain means2.92   –   12.3   n 3.15   –   14.6   n
Mean sample size per strain11.6   mice 11.5   mice


  ANOVA, Q-Q NORMALITY ASSESSMENT
ANOVA summary      
FactorDFSum of squaresMean sum of squaresF valuep value (Pr>F)
sex 1 30.1553 30.1553 0.9188 0.3386
strain 12 1957.8709 163.1559 4.9712 < 0.0001
sex:strain 12 446.2833 37.1903 1.1332 0.3329
Residuals 280 9189.6196 32.8201


Q-Q normality assessment based on residuals

  


  STRAIN MEANS (UNADJUSTED)
  
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Strain Sex Mean SD N mice SEM CV Min, Max Z score
129S1/SvImJ f 2.92 2.41   12 0.694 0.825 -1.56
129S1/SvImJ m 4.1 3.09   12 0.891 0.752 1.0, 11.0 -0.88
A/J f 5.69 3.95   12 1.14 0.695 1.5, 13.5 -0.43
A/J m 8.42 4.83   18 1.14 0.574 2.25, 21.5 0.41
AKR/J f 7.93 4.1   12 1.18 0.517 3.25, 18.2 0.48
AKR/J m 14.6 17.4   12 5.01 1.19 1.5, 67.0 2.26
BALB/cByJ f 5.46 3.07   21 0.669 0.561 2.0, 14.2 -0.53
BALB/cByJ m 5.7 3.12   12 0.901 0.547 2.0, 11.2 -0.4
BALB/cJ f 5.32 4.06   14 1.09 0.764 1.25, 17.0 -0.58
BALB/cJ m 5.43 5.12   10 1.62 0.943 1.5, 16.0 -0.48
C3H/HeJ f 7.58 5.96   10 1.88 0.786 3.5, 22.8 0.34
C3H/HeJ m 7.34 5.1   10 1.61 0.694 2.0, 19.0 0.09
C57BL/6J f 3.25 2.17   11 0.653 0.666 -1.43
C57BL/6J m 3.15 1.1   12 0.318 0.35 1.25, 4.5 -1.16
CAST/EiJ f 8.69 3.83   4 1.91 0.44 4.0, 12.5 0.79
CAST/EiJ m 5.61 4.41   9 1.47 0.787 1.25, 16.2 -0.43
DBA/2J f 6.25 3.24   12 0.936 0.519 2.5, 13.5 -0.2
DBA/2J m 4.14 4.43   11 1.34 1.07 1.0, 15.5 -0.87
FVB/NJ f 12.3 7.63   11 2.3 0.619 5.25, 25.2 2.26
FVB/NJ m 12.7 9.15   12 2.64 0.723 2.25, 25.8 1.69
MOLF/EiJ f 8.1 3.11   12 0.899 0.385 2.67, 14.5 0.55
MOLF/EiJ m 5.64 3.46   11 1.04 0.613 2.25, 13.5 -0.42
SJL/J f 8.0 3.57   12 1.03 0.446 3.0, 13.5 0.51
SJL/J m 6.19 3.17   12 0.916 0.513 2.0, 12.8 -0.25
SM/J f 6.25 5.2   10 1.64 0.831 1.0, 15.5 -0.2
SM/J m 8.54 8.82   12 2.55 1.03 0.25, 27.2 0.45


  LEAST SQUARES MEANS (MODEL-ADJUSTED)
Strain Sex Mean SEM UpperCL LowerCL
129S1/SvImJ f 2.9167 1.6538 6.1721 0.0
129S1/SvImJ m 4.1042 1.6538 7.3596 0.8487
A/J f 5.6875 1.6538 8.9429 2.4321
A/J m 8.4194 1.3503 11.0775 5.7614
AKR/J f 7.9333 1.6538 11.1888 4.6779
AKR/J m 14.5792 1.6538 17.8346 11.3237
BALB/cByJ f 5.4643 1.2501 7.9252 3.0034
BALB/cByJ m 5.7 1.6538 8.9554 2.4446
BALB/cJ f 5.3214 1.5311 8.3354 2.3075
BALB/cJ m 5.43 1.8116 8.9961 1.8639
C3H/HeJ f 7.58 1.8116 11.1461 4.0139
C3H/HeJ m 7.34 1.8116 10.9061 3.7739
C57BL/6J f 3.25 1.7273 6.6502 0.0
C57BL/6J m 3.1458 1.6538 6.4013 0.0
CAST/EiJ f 8.6875 2.8644 14.3261 3.0489
CAST/EiJ m 5.6056 1.9096 9.3646 1.8465
DBA/2J f 6.25 1.6538 9.5054 2.9946
DBA/2J m 4.1364 1.7273 7.5366 0.7362
FVB/NJ f 12.3273 1.7273 15.7275 8.9271
FVB/NJ m 12.6667 1.6538 15.9221 9.4112
MOLF/EiJ f 8.095 1.6538 11.3504 4.8396
MOLF/EiJ m 5.6364 1.7273 9.0366 2.2362
SJL/J f 8.0 1.6538 11.2554 4.7446
SJL/J m 6.1875 1.6538 9.4429 2.9321
SM/J f 6.25 1.8116 9.8161 2.6839
SM/J m 8.5417 1.6538 11.7971 5.2862


  LEAST SQUARES MEANS (MODEL-ADJUSTED), SEXES COMBINED
Strain Sex Mean SEM UpperCL LowerCL
129S1/SvImJ both 3.5104 1.1694 5.8124 1.2085
A/J both 7.0535 1.0675 9.1548 4.9521
AKR/J both 11.2563 1.1694 13.5582 8.9543
BALB/cByJ both 5.5821 1.0366 7.6226 3.5417
BALB/cJ both 5.3757 1.186 7.7103 3.0411
C3H/HeJ both 7.46 1.281 9.9816 4.9384
C57BL/6J both 3.1979 1.1957 5.5516 0.8442
CAST/EiJ both 7.1465 1.7213 10.5349 3.7582
DBA/2J both 5.1932 1.1957 7.5469 2.8395
FVB/NJ both 12.497 1.1957 14.8506 10.1433
MOLF/EiJ both 6.8657 1.1957 9.2194 4.512
SJL/J both 7.0937 1.1694 9.3957 4.7918
SM/J both 7.3958 1.2265 9.8101 4.9815




  GWAS USING LINEAR MIXED MODELS